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Formant frequency fluctuation in stuttering and nonstuttering adults
FORMANT FREQUENCY FLUCTUATION IN STUTTERING AND NONSTUTTERING ADULTS MICHAEL ROBB, MICHAEL BLOMGREN, AND YANG CHEN Department of Communication Sciences, University of Connecticut, Storrs, CT, USA
Inferences were made regarding the vocal tract stability of stutterers’ and nonstutterers’ fluent speech through the examination of formant frequency fluctuation (FFF). Fifteen adult males served as subjects comprising separate groups of untreated stutterers, stutterers enrolled in a fluency-shaping treatment program, and nonstuttering controls. The steady-state portion of formant 2 (F2) was examined in the production of various CVC tokens and evaluated by examining the absolute Hz difference in F2 across consecutive glottal periods. Results of the acoustic analysis indicated a trend in FFF across the three groups. The untreated stutterers displayed the greatest FFF, followed by the control group, with the treated stutterers displaying the most F2 stability. Discussion focuses on the vocal tract stability displayed by each group, as well as the influence of a fluency-shaping treatment program to achieve perceptually fluent speech. © 1998 Elsevier Science Inc.
INTRODUCTION Over the past 30 years, there has been continued interest in examining the vowel formant frequency characteristics of individuals who stutter (e.g., Howell & Vause, 1986; Klich & May, 1982; Metz, Onufrak, & Ogburn, 1979; Prosek et al., 1987; Stromsta, 1965). Because formant frequencies provide information concerning vocal tract geometry, inferences are made concerning the position of the tongue body inside the oral cavity during the production of vowels (Stevens & House, 1955). A common method of acoustically examining vowel formants is within a consonant 1 vowel (CV) or consonant 1 vowel 1 consonant (CVC) syllable context. Using a context such as this allows the vowel to be divided into at least two distinct parts: (1) the formant transition which reflects changes in vocal tract shape immediately following or preceding consonant articulation (Kent & Read, 1992), and (2) the formant steady-state which is assumed to reflect a fixed vocal tract posture specific to the vowel (Peterson & Barney, 1952).
Address correspondence to M.P. Robb, Ph.D., Department of Communication Sciences, University of Connecticut, 850 Bolton Road, U-85, Storrs, CT 06269, USA. e-mail: [email protected]
J. FLUENCY DISORD. 23 (1998), 73–84 © 1998 Elsevier Science Inc. All rights reserved. 655 Avenue of the Americas, New York, NY 10010
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Data regarding formant transitions in the dysfluent speech of children and adults indicate that the pattern of second formant (F2) transitions is variable. The F2 transitions are sometimes absent or atypical (Howell & Vause, 1986; Stromsta, 1986; Yaruss & Conture, 1993), and when they are appropriate they tend to be short in duration (Yaruss & Conture, 1993). Abnormal F2 transitions have also been observed in the perceptually fluent speech of stutterers (Howell & Vause, 1986; Robb & Blomgren, 1997, Zimmermann, 1980). Although past studies vary with regard to analysis methods and speech samples, they seem to confirm that individuals who stutter experience difficulty transitioning from one speech sound to the next. In accord with these findings, treatment approaches that address smooth, deliberate articulatory transitions have shown improvements in speech fluency (e.g., Webster, 1975). Far less research exists pertaining to formant steady-state features of dysfluent speakers. Klich and May (1982) examined the steady-state F1 and F2 values characterizing the fluent CVC productions of seven adults who stuttered. The authors found the stutterers’ F1 and F2 values to be more centralized compared to nonstutterers, which were interpreted to reflect restricted articulatory adjustments used by the stutterers to “control” speech fluency. That is, fluent speech could be more easily maintained by producing vowels using a neutral vocal tract posture within the oral cavity. However, Klich and May’s findings were challenged by Prosek et al. (1987) who examined formant steady-states in both fluent and dysfluent CVC samples among a group of 15 adult stutterers. Contrary to Klich and May, Prosek et al. failed to find formant centralization in either fluent or dysfluent utterances across the subjects. While the Klich and May (1982) and Prosek et al. (1987) studies differ in the assignment of specific F1 and F2 values for various vowels, neither seems to question the stability of steady-state vowels produced by stutterers. Recall that research pertaining to formant transitions has tended to focus on the movement characteristics (i.e., rate and extent) associated with transitioning from one sound to the next. The motor steadiness of vowel steady-states produced by stutterers has received limited attention. Newman, Harris, and Hilton (1989) evaluated fundamental frequency (F0) perturbation in the sustained vowel productions of stutterers and nonstutterers. The authors found clear differences between groups for cycle-to-cycle variations in both frequency (jitter) and amplitude (shimmer). The differences in F0 perturbation were thought to reflect difficulty by the stutterers in maintaining a fixed laryngeal posture during vowel steady-state production. The Newman et al. (1989) findings concerning differences between stutterers and nonstutterers in the laryngeal behavior (i.e., F0 perturbation) of their steady-state productions would suggest that differences may also be apparent in the supralaryngeal (e.g., formant frequency) behavior characterizing vowel steady-states. A tacit assumption concerning the formant frequency characteristics of stutterers’ fluent speech is that abnormal vocal tract adjustments only
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occur during formant transitions while the steady-state portion reflects minimal variation in vocal tract configuration. Presently, there is an absence of data related to the formant stability of steady-state vowel productions. The purpose of this study was to use a relatively unknown acoustic metric, formant frequency fluctuation (FFF), to inferentially evaluate vocal tract stability in the steady-state vowel productions of normally fluent and dysfluent adults. The FFF metric was originally conceived by Gerratt (1983). The measure is based on the premise that a change in vocal tract configuration can be measured as a temporal change in formant frequency. To the extent that the vocal tract remains fixed during a steady-state vowel, little sequential variation in formant frequency would be expected to occur. Thus FFF is an overall assessment of the variation in formant frequency across a defined period of time. Gerratt (1983) employed the FFF metric to evaluate the vocal tract stability in five dysarthric adults compared to 10 normal adults. Results showed that FFF for the dysarthric subjects was significantly larger compared to the normal subjects, indicating less vocal tract stability during vowel production among the dysarthric speakers. The FFF measure reported by Gerratt provides an objective means to evaluate the steady-state vowel characteristics of normal and disordered speakers. The purpose of the present study was to examine FFF in the steady-state vowel productions of normally fluent and dysfluent adults. Assuming the fluent speech of individuals who stutter is marked by abnormal F2 transitions, one might also expect F2 abnormalities to extend beyond the formant transition into the F2 steady-state. It was hypothesized that persons who stutter would differ from normally fluent speakers in the F2 stability of their vowel steady-state productions as a result of disordered motor steadiness within the vocal tract.
METHOD Subjects Fifteen adult males served as subjects in the study. Each subject was categorized as belonging to one of three groups. The first group consisted of five untreated stutterers with an average age of 28 years (R 5 19–41 years of age). The untreated stutterers were those subjects who reported they had not been enrolled in a formal treatment program within the past 5 years. The second group consisted of five treated stutterers with an average age of 27 years (R 5 15–33 years). Each treated stutterer had received a minimum of 100 hours of fluency-shaping therapy (Webster, 1975) within the past 5 years. The treated stutterers were presently enrolled in a 1-week fluency “refresher” program and were implementing therapy techniques at the time of data collection. The basic premise of the refresher program was to emphasize five fluency-facilitating targets: (1) controlled speech rate, (2) gentle phonatory onset, (3) light
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articulatory contacts, (4) use of diaphragmatic breathing, and (5) continuous phonation. The last group consisted of five nonstuttering males with an average age of 35 years (R 5 26–45 years) who served as experimental controls. Stuttering frequency of the untreated and treated stutterers was based on percent-dysfluent analysis of a 200-word spontaneous speech sample collected for each subject. Within-word dysfluencies (i.e., part-word repetitions and [in]audible prolongations) were identified as instances of stuttering. Classification of stuttering severity was based on the eight-point Iowa Scale for Rating Severity of Stuttering (Johnson, Darley, & Spriestersbach, 1963). Among the untreated stutterers, three were classified as severe, one was classified as moderate-to-severe, and one was moderately dysfluent. Among the treated stutterers, four were classified as normally fluent and one was classified as mildly dysfluent. Diagnosis of stuttering was agreed upon by two of the researchers (MR & MB) who are certified speech–language pathologists. All stuttering and nonstuttering subjects were native English speakers with normal hearing and no reported voice or speech articulation disorders at the time of recording. The general characteristics of the subjects are listed in Table 1.
Recording Procedures Audio recordings were obtained from each subject for the production of consonant 1 vowel 1 /t/ (CVt) tokens. The tokens consisted of two word-initial bilabial stops /p, b/, and two alveolar fricatives /s, z/. All tokens ended with the phoneme /t/. The particular word-initial consonants were chosen because they represented variations along voicing, place, and manner of articulation categories. Each consonant was paired with the vowels /i, u, ɑ/, combining for a total of 12 tokens. Each token was embedded within the phrase, “Say CVt again” and randomly presented by means of 537 index cards. Perceptually fluent productions of each CVt token were desired, therefore, all phrases were produced a minimum of three times by each subject to increase the likelihood of fluent productions. Subjects were required to orally read each card using a Table 1. General Characteristics of the Normally Fluent Control Group (C), Untreated Stuttering Subjects (U), and Treated Stuttering Subjects (T)a C-Group U-Group Dysfluency (Age-yr) (Age-yr) (%) C1 (26) C2 (30) C3 (34) C4 (40) C5 (45)
U1 (19) U2 (19) U3 (26) U4 (34) U5 (41)
10% 20% 6% 23% 20%
Severity Moderate-Severe Severe Moderate Severe Severe
T-Group Dysfluency (Age-yr) (%) Severity T1 (15) T2 (27) T3 (30) T4 (30) T5 (33)
3% 3% 3% 3% 5%
Normal Normal Normal Normal Mild
a The percent-dysfluency and stuttering severity ratings for the U and T subjects are based on analysis of a 200-word sample as per Johnson, Darley, and Spriestersbach (1963).
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comfortable loudness level and speaking rate. Audio recordings of the CVt samples were obtained in an acoustically treated sound booth. An audiocassette deck (Akai CS-340 or Marantz PMD-430) and dynamic microphone (Spherodyne 533SA) were used to record each subject’s speech productions. A mouth to microphone distance of approximately 15 cm was maintained during recording. Following collection of the samples, each CVt phrase was perceptually evaluated for fluency on each word of the phrase by one of the researchers. In order for a CVt to be targeted for acoustic analysis, the entire phrase needed to be produced fluently and correctly articulated. Selection of fluent phrases was also based on confirmation provided by each subject. Those instances when disagreement occurred between researcher and subject concerning fluency were handled by discarding those questionable phrases. Assuming all tokens were produced fluently, a minimum of 36 tokens could be collected from each subject within each group for a total of 180 tokens per group (12 tokens 3 3 repetitions 3 5 subjects). On the basis of these requirements, approximately 20% of the CVt phrases were discarded. Additional reasons for discarding tokens included poor signal-to-noise ratio and voice overlap between the subject and researcher. Across the three groups, a total of 145, 147, and 143 fluent CVt phrases were collected for the untreated stutterers, treated stutterers, and nonstutterers, respectively.
Acoustic Analysis The acoustic analysis was performed using an integrated computer hardware/ software system which permitted digitization, editing, and storage of CVt samples (Kay CSL-4300). Each CVt token was fed from a cassette deck (Nakamichi MR2) into a computer (80586 cpu) and digitized at 16 kHz with 16-bit quantization. Each CVt was subsequently displayed as a “raw” amplitude-bytime waveform on a computer monitor. Once the raw waveform was displayed, a single vertical cursor was manually positioned beyond the prevocalic consonant and the ensuing vowel F2 transition to demarcate the onset of the vowel steady-state. The beginning of the vowel steady-state was predetermined at 40 msec after the onset of vowel quasi-periodicity.1 1Unlike previous researchers who used visual criteria for noting the onset and offset of steady-state vowels (Klich & May, 1982; Yaruss & Conture, 1993), the present research employed a fixed time-point criterion. Nearey and Shammass (1987) advocate a fixed time-point to isolate vowel steady-states as a means of increasing the objectivity and reliability of acoustic measurement. Selection of a 40-msec steady-state vowel onset criteria was based on trial and error manipulation of the LPC analysis scheme using a variety of CVt tokens. These trials involved obtaining wideband (300-Hz filter) spectrograms of CVt tokens which were magnified to allow clear identification of the glottal cycles comprising the vowel. Once a spectrogram was displayed, the vowel steady-state onset was visually demarcated at various points along the F2 of the vowel and the LPC analysis was overlaid on the spectrogram as a form of verification. Based on these trials, we determined that the status of the vowel at 40-msec post-vowel onset was well beyond the confounding influence of the initial F2 transition. The influence of the postvocalic /t/ was not considered in the present study. Determining a specific steady-state offset would have greatly reduced the number of analyzable pitch periods for calculation of FFF.
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The present study measured FFF by moving the vertical cursor forward (beginning at the 40-msec steady-state onset point) in synchronous (cycle-tocycle) fashion, covering each successive pitch period. At each pitch period, a 12-coefficient linear predictive coding (LPC) analysis was performed to provide an amplitude-by-frequency visual and numeric display of spectral energy. The midpoint of the second spectral peak was judged to represent the F2 for that pitch period.2 The analysis scheme allowed for measurement of a minimum of five pitch periods (i.e., five F2 values) up to a maximum of ten pitch periods (i.e., ten F2 values) across a steady-state vowel. The FFF measure was calculated for each vowel as the difference in Hz among the consecutive (absolute) F2 values and computed as the average of the differences.3 Overall F2 was also calculated for each steady-state vowel by taking an average of the consecutive F2 values. In addition to analyzing F2, the vowel nuclei duration of each CVt token was measured. Vowel duration was measured by superimposing a pair of vertical cursors on the amplitude-by-time display and demarcating the onset and offset of vowel periodicity. Intrajudge reliability for calculation of FFF and vowel duration was based on a complete reanalysis of the CVt samples for one subject from each of the three groups (86 CVt tokens in total). The average remeasurement differences for FFF between the original measurements and remeasurements for the control group, treatment group, and untreated stuttering group were 25 Hz, 33 Hz, and 33 Hz, respectively. The remeasurement differences for vowel duration in the control group, treatment group, and untreated stuttering group samples were 10 ms, 6 ms, and 8 ms, respectively.
2A major consideration in the use of LPC is the number of prediction coefficients selected to model the vocal tract. If too many coefficients are computed, then spurious peaks that do not represent formants may appear. Whereas, if too few coefficients are used, true formants may be missed (Kent & Read, 1992). Generally, an adult male vocal tract is satisfactorily modeled using 12–14 coefficients (Hillenbrand et al., 1995). The present LPC analysis was based on a 12-coefficient model calculated across Hamming-windowed segments. Subsequent comparison of the average F2 values obtained for the control group (n 5 5) to those values reported by Hillenbrand et al. indicated a 3-Hz difference for /i/ tokens, 99 Hz difference for /a/ tokens, and a 146 Hz difference for /u/ tokens. Considering the small number of subjects in the present study and the various CVt contexts examined, we took these findings to indicate that our acoustic analysis method yielded accurate estimates of formant frequencies. 3Gerratt (1983) calculated two measures of FFF. The first was mean (absolute) FFF which is identical to the measurements performed in the present study. The second measure was a FFF ratio which was based on taking the mean FFF and dividing it by the mean F2 frequency. The FFF ratio measure is calculated in a manner similar to that performed for F0 perturbation (Newman et al., 1989). It is important to note that Gerratt examined both males and females which necessitated the use of the FFF ratio to normalize across speakers of different vocal tract lengths. The present study was confined to adult male speakers and, therefore, transformation of the data to a FFF ratio was deemed unnecessary.
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RESULTS Average F2 According to Phonetic Context. The average F2 values for each CVt token produced by each group are listed in Table 2. The group results were calculated by collapsing the F2 values for each CVt token produced by each subject within a group. Across 10 of 12 CVt tokens, the highest F2 values were found for the group of treated stutterers. The lowest F2 values were found for the untreated stutterers across 11 of 12 CVt tokens. A series of one-way analysis of variance (ANOVA) tests were performed on the group data to determine whether the average F2 for each CVt token significantly differed across the three subject groups. The multiple ANOVA comparisons necessitated adjusting the alpha level to maintain an experiment-wise error rate of p , 0.05 (Kirk, 1982). Significant differences in average F2 were found across groups for production of /pit/ [F (2,41) 5 8.89, p , 0.05] and /zit/ [F (2,40) 5 8.89, p , 0.05]. Post-hoc Scheffe t tests indicated that F2 values were significantly lower in the untreated stutterers compared to the controls (two-tailed, p , 0.05), and compared to the treated stutterers (two-tailed, p , 0.05) for both /pit/ and /zit/ productions. Overall F2. The overall group F2 values collapsed across all CVt tokens are listed in Table 2. The overall F2 for the control group was 1581 Hz (Sd 5 503 Hz). The overall F2 values for the groups of untreated and treated stutterers were 1462 Hz (Sd 5 469 Hz) and 1627 Hz (Sd 5 512 Hz), respectively. Table 2. Average Second Formant Frequency (F2) and Formant Frequency Fluctuation (FFF) in Hz, for the Control Group (C), Untreated Stuttering Subjects (U), and Treated Stuttering Subjects (T)a C-Group Token
U-Group
T-Group
F2
FFF
F2
FFF
F2
FFF
/pit/ /put/ /pat/ /bit/ /but/ /bat/ /sit/ /sut/ /sat/ /zit/ /zut/ /zat/
2235 (169) 1239 (119) 1234 (142) 2240 (247) 1035 (146) 1196 (310) 2285 (187) 1331 (358) 1231 (271) 2239 (194) 1459 (306) 1249 (96)
133 (35) 139 (89) 131 (83) 142 (61) 101 (62) 152 (98) 153 (62) 109 (52) 114 (79) 144 (76) 104 (95) 142 (115)
2061 (196) 977 (171) 1330 (87) 2115 (206) 955 (144) 1102 (157) 2098 (233) 1097 (174) 1207 (189) 2028 (177) 1390 (183) 1194 (121)
157 (92) 217 (126) 80 (58) 167 (103) 134 (71) 116 (82) 209 (128) 186 (86) 109 (117) 183 (114) 184 (109) 147 (80)
2287 (143) 1106 (143) 1261 (154) 2281 (158) 1041 (114) 1287 (206) 2291 (124) 1581 (296) 1279 (189) 2320 (169) 1479 (283) 1322 (106)
140 (100) 102 (69) 81 (77) 120 (65) 72 (64) 114 (117) 132 (68) 111 (68) 66 (38) 135 (77) 141 (101) 77 (42)
M5
1581 (503)
131 (78)
1462 (469)
160 (104)
1627 (512)
108 (90)
a Standard
deviation values are shown in parentheses.
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Average FFF According to Phonetic Context. The average FFF values for each CVt token across each subject group are listed in Table 2. The largest FFF was found among the untreated stutterers across nine of the 12 CVt tokens. The exceptions were /pat/, /bat/, and /sat/, which showed smaller FFF compared to the nonstuttering control group. The smallest FFF was found among the treated stutterers across nine of the 12 CVt tokens. The exceptions to this pattern were the /pit/, /sut/, and /zut/ tokens which showed the smallest FFF among the control group. A series of alpha-adjusted ANOVAs were performed to determine whether the FFF of each CVt token significantly differed across the three subject groups. The main effect was significant for /put/ [F (2,42) 5 5.06, p , 0.05)], /sit/ [F (2,42) 5 4.80, p , 0.05], and /zat/ [F (2,42) 5 4.91, p , 0.05]. Post-hoc Scheffe t tests identified a significantly smaller FFF (two-tailed, p , 0.05) among the treated stutterers compared to the untreated stutterers for production of the /put, sit, zat/ tokens. In addition, treated stutterers displayed a smaller FFF compared to the control group for production of /zat/ (two-tailed, p , 0.05). Overall FFF. The overall FFF results for each group are listed in Table 2. The group results were calculated by collapsing the FFF values for each CVt token produced by each subject within a group. In general, the pattern of FFF found for the individual CVt tokens was evident for the overall group data. The smallest overall FFF was found among the treated stutterers (M 5 108.0 Hz), followed by the control group (M 5 131.4 Hz). The largest overall FFF was found for the untreated stutterers (M 5 160.3 Hz). The overall variability in FFF was roughly similar between the treated stutterers (Sd 5 80.1 Hz) and control group (Sd 5 78.9). The largest overall variability in FFF was found for the untreated stutterers (Sd 5 104.5). A one-way ANOVA was performed on the group data to determine whether overall FFF significantly differed across the three subject groups. The main effect was significant [F (2,432) 5 12.53, p , 0.05]. Post-hoc Sheffe t tests identified a significantly larger overall FFF among the untreated stutterers compared to the control group (two-tailed, p , 0.05), and compared to the treated stutterers (twotailed, p , 0.05). There were no significant differences in overall FFF between the control group and the treated stutterers.
Vowel Durations According to Phonetic Context. The average vowel duration values for each CVt token across each subject group are listed in Table 3. Across the 12 CVt tokens, the shortest vowel durations were consistently noted for the control group. The longest vowel durations were observed for the group of treated stutterers. The only exception to this pattern was identified for the /pat/ token
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which was slightly longer for the untreated stutterers. A series of alpha-adjusted ANOVAs were performed to determine whether the average vowel duration of each CVt token significantly differed across the three subject groups. Although a general pattern of vowel durations was observed across the groups, results of the ANOVA testing failed to find significant differences for any of the CVt tokens. Overall Durations. The overall vowel durations for each group are listed in Table 3. The shortest vowel durations were observed for the control group (M 5 173 ms), followed by the group of untreated stutterers (M 5 203 ms). The longest vowel durations were found for the group of treated stutterers (M 5 217 ms).
DISCUSSION The above results and ensuing interpretations should be viewed with caution. The number of subjects and speech tokens considered in the analysis were small which contributed to an FFF measurement error approximating the effect size. Because of the small database, sufficient statistical power to detect group differences could not be fully ensured (Kirk, 1982). In light of these limitations, group differences were noted in the stability of F2. Untreated stutterers consistently showed the largest FFF for production of a majority of the CVt tokens, while the treated stutterers showed the smallest FFF across tokens.
Table 3. Average Vowel Duration (in msec) of Each CVt Token for the Control Group (C), Untreated Stuttering Subjects (U), and Treated Stuttering Subjects (T) Vowel Duration Token
C-Group
U-Group
T-Group
/pit/ /put/ /pat/ /bit/ /but/ /bat/ /sit/ /sut/ /sat/ /zit/ /zut/ /zat/
144 (27) 152 (22) 162 (16) 176 (32) 174 (26) 196 (33) 152 (21) 156 (30) 186 (41) 192 (38) 196 (35) 198 (43)
182 (45) 167 (30) 197 (37) 212 (63) 210 (37) 212 (20) 195 (44) 200 (100) 207 (29) 212 (18) 190 (42) 217 (41)
186 (69) 194 (58) 196 (53) 236 (69) 230 (81) 230 (35) 202 (73) 202 (60) 212 (47) 228 (70) 244 (68) 246 (39)
M5
173 (34)
203 (49)
217 (59)
Standard deviations are shown in parentheses.
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The small FFF across the treated stutterers is most likely attributable to the effects of fluency-shaping therapy. Pre-therapy CVt samples were not obtained from these subjects which would have allowed for direct examination of treatment effects on FFF. Still, particular features of the fluency refresher program received by these subjects emphasized controlled speech rate, light articulatory contacts, and continuous phonation (Webster, 1975). It is interesting to note that in addition to demonstrating the smallest FFF, the group of treated stutterers also displayed the longest vowel durations and highest average F2 values. Taken as a whole, these findings would indicate a rather complex pattern of speech motor control associated with the maintenance of speech fluency among the treated stutterers. While the present study was concerned with evaluating vocal tract stability using the FFF measure, a comment is warranted regarding the possible clinical utility of this measure. Assuming FFF provides an inferential estimate of vocal tract stability (Gerratt, 1983), it may also serve as a sensitive measure of speech fluency. For example, consider the overall differences in FFF across the three subject groups. The FFF for the untreated stutterers was approximately 30 Hz larger compared to the nonstuttering control group, and over 50 Hz larger than the treated stutterers. In other words, the untreated stutterers demonstrated the most vocal tract instability in what were perceived to be fluent CVt productions. It is possible that the FFF measure was revealing of speech dysfluency which was not perceptually identifiable (cf., Armson & Kalinowski, 1994). An interesting test of the FFF measure would be to compare the FFF characteristics of perceptually dysfluent speech to perceptually fluent speech to note whether vocal tract stability varies as a function of perceived speech fluency. In conclusion, past research examining F2 transitions has shown that stutterers experience difficulty in transitioning from one speech sound to the next in CVC contexts (Robb & Blomgren, 1997; Yaruss & Conture, 1993). To the extent that FFF serves as a measure of vocal tract stability, the present findings indicate that disordered articulation is also manifest in the steady-state portion of vowels. Using refined methods of acoustic analysis such as FFF, it is becoming increasingly clear that the fluent speech of stutterers is more different than similar to that of normally fluent individuals. We wish to thank Drs. Jay Lerman and Robert Prosek who provided comments on early versions of this manuscript.
REFERENCES Armson, J. & Kalinowski, J. (1994). Interpreting results from the fluent speech paradigm in stuttering research: Difficulties in separating cause from effect. Journal of Speech and Hearing Research 37, 69–82.
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Gerratt, B. (1983). Formant frequency fluctuation as an index of motor steadiness in the vocal tract. Journal of Speech and Hearing Research 26, 297– 304. Hillenbrand, J., Getty, L., Clark, M., & Wheeler, K. (1995). Acoustic characteristics of American English vowels. Journal of the Acoustical Society of America 97, 3099–3111. Howell, P. & Vause, L. (1986). Acoustic analysis and perception of vowels in stuttered speech. Journal of the Acoustical Society of America 79, 1571– 1579. Johnson, W., Darley, D., & Spriestersbach, D. (1963). Diagnostic Methods in Speech Pathology. New York: Harper & Row. Kent, R. & Read, C. (1992). The Acoustic Analysis of Speech. San Diego, CA: Singular Publishing Inc. Kirk, R. (1982). Experimental Design: Procedures for the Behavioral Sciences (2nd Ed.). Belmont, CA: Brooks/Cole Publishing Co. Klich, R. & May, G. (1982). Spectrographic study of vowels in stutterers’ fluent speech. Journal of Speech and Hearing Research 25, 364–370. Metz, D., Onufrak, J., & Ogburn, S. (1979). An acoustical analysis of stutterers speech prior to and at the termination of therapy. Journal of Fluency Disorders 4, 249–254. Nearey, T. & Shammass, S. (1987). Formant transitions as partly distinctive invariant properties in the identification of stops. Canadian Acoustics 15, 17–24. Newman, P., Harris, R., & Hilton, L. (1989). Vocal jitter and shimmer in stuttering. Journal of Fluency Disorders 14, 87–95. Peterson, G. & Barney, H. (1952). Control methods used in a study of vowels. Journal of the Acoustical Society of America 24, 173–184. Prosek, R., Montgomery, A., Walden, B., & Hawkins, D. (1987). Formant frequencies of stuttered and fluent vowels. Journal of Speech and Hearing Research 30, 301–305. Robb, M. & Blomgren, M. (1997). Analysis of F2 transitions in the speech of stutterers and nonstutterers. Journal of Fluency Disorders 22, 1–16. Stevens, K. & House, A. (1955). Development of a description of vowel articulation. Journal of the Acoustical Society of America 27, 484–493. Stromsta, C. (1965). A spectrographic study of dysfluencies labeled as stuttering by parents. De Therapia Vocis et Loquelae. Proceedings of the 13th Congress of the International Association of Logopedics and Phoniatrics, Vienna, 1, 317–320. Stromsta, C. (1986). Elements of Stuttering. Oshtemo, MI: Atsmonts Publishing.
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Webster, R. (1975). The precision fluency shaping program: Speech reconstruction for stutterers. Roanoke, VA: Communications Development Corp. Yaruss, J. & Conture, E. (1993). F2 transition during sound/syllable repetitions of children who stutter and predictions of stuttering chronicity. Journal of Speech and Hearing Research 36, 883–896. Zimmermann, G. (1980). Articulatory dynamics of fluent utterances of stutterers and non-stutterers. Journal of Speech and Hearing Research 23, 95–107.
Inferences were made regarding the vocal tract stability of stutterers’ and nonstutterers’ fluent speech through the examination of formant frequency fluctuation (FFF). Fifteen adult males served as subjects comprising separate groups of untreated stutterers, stutterers enrolled in a fluency-shaping treatment program, and nonstuttering controls. The steady-state portion of formant 2 (F2) was examined in the production of various CVC tokens and evaluated by examining the absolute Hz difference in F2 across consecutive glottal periods. Results of the acoustic analysis indicated a trend in FFF across the three groups. The untreated stutterers displayed the greatest FFF, followed by the control group, with the treated stutterers displaying the most F2 stability. Discussion focuses on the vocal tract stability displayed by each group, as well as the influence of a fluency-shaping treatment program to achieve perceptually fluent speech. © 1998 Elsevier Science Inc.
INTRODUCTION Over the past 30 years, there has been continued interest in examining the vowel formant frequency characteristics of individuals who stutter (e.g., Howell & Vause, 1986; Klich & May, 1982; Metz, Onufrak, & Ogburn, 1979; Prosek et al., 1987; Stromsta, 1965). Because formant frequencies provide information concerning vocal tract geometry, inferences are made concerning the position of the tongue body inside the oral cavity during the production of vowels (Stevens & House, 1955). A common method of acoustically examining vowel formants is within a consonant 1 vowel (CV) or consonant 1 vowel 1 consonant (CVC) syllable context. Using a context such as this allows the vowel to be divided into at least two distinct parts: (1) the formant transition which reflects changes in vocal tract shape immediately following or preceding consonant articulation (Kent & Read, 1992), and (2) the formant steady-state which is assumed to reflect a fixed vocal tract posture specific to the vowel (Peterson & Barney, 1952).
Address correspondence to M.P. Robb, Ph.D., Department of Communication Sciences, University of Connecticut, 850 Bolton Road, U-85, Storrs, CT 06269, USA. e-mail: [email protected]
J. FLUENCY DISORD. 23 (1998), 73–84 © 1998 Elsevier Science Inc. All rights reserved. 655 Avenue of the Americas, New York, NY 10010
0094-730X/98/$19.00 PII S0094-730X(97)00029-6
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Data regarding formant transitions in the dysfluent speech of children and adults indicate that the pattern of second formant (F2) transitions is variable. The F2 transitions are sometimes absent or atypical (Howell & Vause, 1986; Stromsta, 1986; Yaruss & Conture, 1993), and when they are appropriate they tend to be short in duration (Yaruss & Conture, 1993). Abnormal F2 transitions have also been observed in the perceptually fluent speech of stutterers (Howell & Vause, 1986; Robb & Blomgren, 1997, Zimmermann, 1980). Although past studies vary with regard to analysis methods and speech samples, they seem to confirm that individuals who stutter experience difficulty transitioning from one speech sound to the next. In accord with these findings, treatment approaches that address smooth, deliberate articulatory transitions have shown improvements in speech fluency (e.g., Webster, 1975). Far less research exists pertaining to formant steady-state features of dysfluent speakers. Klich and May (1982) examined the steady-state F1 and F2 values characterizing the fluent CVC productions of seven adults who stuttered. The authors found the stutterers’ F1 and F2 values to be more centralized compared to nonstutterers, which were interpreted to reflect restricted articulatory adjustments used by the stutterers to “control” speech fluency. That is, fluent speech could be more easily maintained by producing vowels using a neutral vocal tract posture within the oral cavity. However, Klich and May’s findings were challenged by Prosek et al. (1987) who examined formant steady-states in both fluent and dysfluent CVC samples among a group of 15 adult stutterers. Contrary to Klich and May, Prosek et al. failed to find formant centralization in either fluent or dysfluent utterances across the subjects. While the Klich and May (1982) and Prosek et al. (1987) studies differ in the assignment of specific F1 and F2 values for various vowels, neither seems to question the stability of steady-state vowels produced by stutterers. Recall that research pertaining to formant transitions has tended to focus on the movement characteristics (i.e., rate and extent) associated with transitioning from one sound to the next. The motor steadiness of vowel steady-states produced by stutterers has received limited attention. Newman, Harris, and Hilton (1989) evaluated fundamental frequency (F0) perturbation in the sustained vowel productions of stutterers and nonstutterers. The authors found clear differences between groups for cycle-to-cycle variations in both frequency (jitter) and amplitude (shimmer). The differences in F0 perturbation were thought to reflect difficulty by the stutterers in maintaining a fixed laryngeal posture during vowel steady-state production. The Newman et al. (1989) findings concerning differences between stutterers and nonstutterers in the laryngeal behavior (i.e., F0 perturbation) of their steady-state productions would suggest that differences may also be apparent in the supralaryngeal (e.g., formant frequency) behavior characterizing vowel steady-states. A tacit assumption concerning the formant frequency characteristics of stutterers’ fluent speech is that abnormal vocal tract adjustments only
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occur during formant transitions while the steady-state portion reflects minimal variation in vocal tract configuration. Presently, there is an absence of data related to the formant stability of steady-state vowel productions. The purpose of this study was to use a relatively unknown acoustic metric, formant frequency fluctuation (FFF), to inferentially evaluate vocal tract stability in the steady-state vowel productions of normally fluent and dysfluent adults. The FFF metric was originally conceived by Gerratt (1983). The measure is based on the premise that a change in vocal tract configuration can be measured as a temporal change in formant frequency. To the extent that the vocal tract remains fixed during a steady-state vowel, little sequential variation in formant frequency would be expected to occur. Thus FFF is an overall assessment of the variation in formant frequency across a defined period of time. Gerratt (1983) employed the FFF metric to evaluate the vocal tract stability in five dysarthric adults compared to 10 normal adults. Results showed that FFF for the dysarthric subjects was significantly larger compared to the normal subjects, indicating less vocal tract stability during vowel production among the dysarthric speakers. The FFF measure reported by Gerratt provides an objective means to evaluate the steady-state vowel characteristics of normal and disordered speakers. The purpose of the present study was to examine FFF in the steady-state vowel productions of normally fluent and dysfluent adults. Assuming the fluent speech of individuals who stutter is marked by abnormal F2 transitions, one might also expect F2 abnormalities to extend beyond the formant transition into the F2 steady-state. It was hypothesized that persons who stutter would differ from normally fluent speakers in the F2 stability of their vowel steady-state productions as a result of disordered motor steadiness within the vocal tract.
METHOD Subjects Fifteen adult males served as subjects in the study. Each subject was categorized as belonging to one of three groups. The first group consisted of five untreated stutterers with an average age of 28 years (R 5 19–41 years of age). The untreated stutterers were those subjects who reported they had not been enrolled in a formal treatment program within the past 5 years. The second group consisted of five treated stutterers with an average age of 27 years (R 5 15–33 years). Each treated stutterer had received a minimum of 100 hours of fluency-shaping therapy (Webster, 1975) within the past 5 years. The treated stutterers were presently enrolled in a 1-week fluency “refresher” program and were implementing therapy techniques at the time of data collection. The basic premise of the refresher program was to emphasize five fluency-facilitating targets: (1) controlled speech rate, (2) gentle phonatory onset, (3) light
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articulatory contacts, (4) use of diaphragmatic breathing, and (5) continuous phonation. The last group consisted of five nonstuttering males with an average age of 35 years (R 5 26–45 years) who served as experimental controls. Stuttering frequency of the untreated and treated stutterers was based on percent-dysfluent analysis of a 200-word spontaneous speech sample collected for each subject. Within-word dysfluencies (i.e., part-word repetitions and [in]audible prolongations) were identified as instances of stuttering. Classification of stuttering severity was based on the eight-point Iowa Scale for Rating Severity of Stuttering (Johnson, Darley, & Spriestersbach, 1963). Among the untreated stutterers, three were classified as severe, one was classified as moderate-to-severe, and one was moderately dysfluent. Among the treated stutterers, four were classified as normally fluent and one was classified as mildly dysfluent. Diagnosis of stuttering was agreed upon by two of the researchers (MR & MB) who are certified speech–language pathologists. All stuttering and nonstuttering subjects were native English speakers with normal hearing and no reported voice or speech articulation disorders at the time of recording. The general characteristics of the subjects are listed in Table 1.
Recording Procedures Audio recordings were obtained from each subject for the production of consonant 1 vowel 1 /t/ (CVt) tokens. The tokens consisted of two word-initial bilabial stops /p, b/, and two alveolar fricatives /s, z/. All tokens ended with the phoneme /t/. The particular word-initial consonants were chosen because they represented variations along voicing, place, and manner of articulation categories. Each consonant was paired with the vowels /i, u, ɑ/, combining for a total of 12 tokens. Each token was embedded within the phrase, “Say CVt again” and randomly presented by means of 537 index cards. Perceptually fluent productions of each CVt token were desired, therefore, all phrases were produced a minimum of three times by each subject to increase the likelihood of fluent productions. Subjects were required to orally read each card using a Table 1. General Characteristics of the Normally Fluent Control Group (C), Untreated Stuttering Subjects (U), and Treated Stuttering Subjects (T)a C-Group U-Group Dysfluency (Age-yr) (Age-yr) (%) C1 (26) C2 (30) C3 (34) C4 (40) C5 (45)
U1 (19) U2 (19) U3 (26) U4 (34) U5 (41)
10% 20% 6% 23% 20%
Severity Moderate-Severe Severe Moderate Severe Severe
T-Group Dysfluency (Age-yr) (%) Severity T1 (15) T2 (27) T3 (30) T4 (30) T5 (33)
3% 3% 3% 3% 5%
Normal Normal Normal Normal Mild
a The percent-dysfluency and stuttering severity ratings for the U and T subjects are based on analysis of a 200-word sample as per Johnson, Darley, and Spriestersbach (1963).
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comfortable loudness level and speaking rate. Audio recordings of the CVt samples were obtained in an acoustically treated sound booth. An audiocassette deck (Akai CS-340 or Marantz PMD-430) and dynamic microphone (Spherodyne 533SA) were used to record each subject’s speech productions. A mouth to microphone distance of approximately 15 cm was maintained during recording. Following collection of the samples, each CVt phrase was perceptually evaluated for fluency on each word of the phrase by one of the researchers. In order for a CVt to be targeted for acoustic analysis, the entire phrase needed to be produced fluently and correctly articulated. Selection of fluent phrases was also based on confirmation provided by each subject. Those instances when disagreement occurred between researcher and subject concerning fluency were handled by discarding those questionable phrases. Assuming all tokens were produced fluently, a minimum of 36 tokens could be collected from each subject within each group for a total of 180 tokens per group (12 tokens 3 3 repetitions 3 5 subjects). On the basis of these requirements, approximately 20% of the CVt phrases were discarded. Additional reasons for discarding tokens included poor signal-to-noise ratio and voice overlap between the subject and researcher. Across the three groups, a total of 145, 147, and 143 fluent CVt phrases were collected for the untreated stutterers, treated stutterers, and nonstutterers, respectively.
Acoustic Analysis The acoustic analysis was performed using an integrated computer hardware/ software system which permitted digitization, editing, and storage of CVt samples (Kay CSL-4300). Each CVt token was fed from a cassette deck (Nakamichi MR2) into a computer (80586 cpu) and digitized at 16 kHz with 16-bit quantization. Each CVt was subsequently displayed as a “raw” amplitude-bytime waveform on a computer monitor. Once the raw waveform was displayed, a single vertical cursor was manually positioned beyond the prevocalic consonant and the ensuing vowel F2 transition to demarcate the onset of the vowel steady-state. The beginning of the vowel steady-state was predetermined at 40 msec after the onset of vowel quasi-periodicity.1 1Unlike previous researchers who used visual criteria for noting the onset and offset of steady-state vowels (Klich & May, 1982; Yaruss & Conture, 1993), the present research employed a fixed time-point criterion. Nearey and Shammass (1987) advocate a fixed time-point to isolate vowel steady-states as a means of increasing the objectivity and reliability of acoustic measurement. Selection of a 40-msec steady-state vowel onset criteria was based on trial and error manipulation of the LPC analysis scheme using a variety of CVt tokens. These trials involved obtaining wideband (300-Hz filter) spectrograms of CVt tokens which were magnified to allow clear identification of the glottal cycles comprising the vowel. Once a spectrogram was displayed, the vowel steady-state onset was visually demarcated at various points along the F2 of the vowel and the LPC analysis was overlaid on the spectrogram as a form of verification. Based on these trials, we determined that the status of the vowel at 40-msec post-vowel onset was well beyond the confounding influence of the initial F2 transition. The influence of the postvocalic /t/ was not considered in the present study. Determining a specific steady-state offset would have greatly reduced the number of analyzable pitch periods for calculation of FFF.
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The present study measured FFF by moving the vertical cursor forward (beginning at the 40-msec steady-state onset point) in synchronous (cycle-tocycle) fashion, covering each successive pitch period. At each pitch period, a 12-coefficient linear predictive coding (LPC) analysis was performed to provide an amplitude-by-frequency visual and numeric display of spectral energy. The midpoint of the second spectral peak was judged to represent the F2 for that pitch period.2 The analysis scheme allowed for measurement of a minimum of five pitch periods (i.e., five F2 values) up to a maximum of ten pitch periods (i.e., ten F2 values) across a steady-state vowel. The FFF measure was calculated for each vowel as the difference in Hz among the consecutive (absolute) F2 values and computed as the average of the differences.3 Overall F2 was also calculated for each steady-state vowel by taking an average of the consecutive F2 values. In addition to analyzing F2, the vowel nuclei duration of each CVt token was measured. Vowel duration was measured by superimposing a pair of vertical cursors on the amplitude-by-time display and demarcating the onset and offset of vowel periodicity. Intrajudge reliability for calculation of FFF and vowel duration was based on a complete reanalysis of the CVt samples for one subject from each of the three groups (86 CVt tokens in total). The average remeasurement differences for FFF between the original measurements and remeasurements for the control group, treatment group, and untreated stuttering group were 25 Hz, 33 Hz, and 33 Hz, respectively. The remeasurement differences for vowel duration in the control group, treatment group, and untreated stuttering group samples were 10 ms, 6 ms, and 8 ms, respectively.
2A major consideration in the use of LPC is the number of prediction coefficients selected to model the vocal tract. If too many coefficients are computed, then spurious peaks that do not represent formants may appear. Whereas, if too few coefficients are used, true formants may be missed (Kent & Read, 1992). Generally, an adult male vocal tract is satisfactorily modeled using 12–14 coefficients (Hillenbrand et al., 1995). The present LPC analysis was based on a 12-coefficient model calculated across Hamming-windowed segments. Subsequent comparison of the average F2 values obtained for the control group (n 5 5) to those values reported by Hillenbrand et al. indicated a 3-Hz difference for /i/ tokens, 99 Hz difference for /a/ tokens, and a 146 Hz difference for /u/ tokens. Considering the small number of subjects in the present study and the various CVt contexts examined, we took these findings to indicate that our acoustic analysis method yielded accurate estimates of formant frequencies. 3Gerratt (1983) calculated two measures of FFF. The first was mean (absolute) FFF which is identical to the measurements performed in the present study. The second measure was a FFF ratio which was based on taking the mean FFF and dividing it by the mean F2 frequency. The FFF ratio measure is calculated in a manner similar to that performed for F0 perturbation (Newman et al., 1989). It is important to note that Gerratt examined both males and females which necessitated the use of the FFF ratio to normalize across speakers of different vocal tract lengths. The present study was confined to adult male speakers and, therefore, transformation of the data to a FFF ratio was deemed unnecessary.
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RESULTS Average F2 According to Phonetic Context. The average F2 values for each CVt token produced by each group are listed in Table 2. The group results were calculated by collapsing the F2 values for each CVt token produced by each subject within a group. Across 10 of 12 CVt tokens, the highest F2 values were found for the group of treated stutterers. The lowest F2 values were found for the untreated stutterers across 11 of 12 CVt tokens. A series of one-way analysis of variance (ANOVA) tests were performed on the group data to determine whether the average F2 for each CVt token significantly differed across the three subject groups. The multiple ANOVA comparisons necessitated adjusting the alpha level to maintain an experiment-wise error rate of p , 0.05 (Kirk, 1982). Significant differences in average F2 were found across groups for production of /pit/ [F (2,41) 5 8.89, p , 0.05] and /zit/ [F (2,40) 5 8.89, p , 0.05]. Post-hoc Scheffe t tests indicated that F2 values were significantly lower in the untreated stutterers compared to the controls (two-tailed, p , 0.05), and compared to the treated stutterers (two-tailed, p , 0.05) for both /pit/ and /zit/ productions. Overall F2. The overall group F2 values collapsed across all CVt tokens are listed in Table 2. The overall F2 for the control group was 1581 Hz (Sd 5 503 Hz). The overall F2 values for the groups of untreated and treated stutterers were 1462 Hz (Sd 5 469 Hz) and 1627 Hz (Sd 5 512 Hz), respectively. Table 2. Average Second Formant Frequency (F2) and Formant Frequency Fluctuation (FFF) in Hz, for the Control Group (C), Untreated Stuttering Subjects (U), and Treated Stuttering Subjects (T)a C-Group Token
U-Group
T-Group
F2
FFF
F2
FFF
F2
FFF
/pit/ /put/ /pat/ /bit/ /but/ /bat/ /sit/ /sut/ /sat/ /zit/ /zut/ /zat/
2235 (169) 1239 (119) 1234 (142) 2240 (247) 1035 (146) 1196 (310) 2285 (187) 1331 (358) 1231 (271) 2239 (194) 1459 (306) 1249 (96)
133 (35) 139 (89) 131 (83) 142 (61) 101 (62) 152 (98) 153 (62) 109 (52) 114 (79) 144 (76) 104 (95) 142 (115)
2061 (196) 977 (171) 1330 (87) 2115 (206) 955 (144) 1102 (157) 2098 (233) 1097 (174) 1207 (189) 2028 (177) 1390 (183) 1194 (121)
157 (92) 217 (126) 80 (58) 167 (103) 134 (71) 116 (82) 209 (128) 186 (86) 109 (117) 183 (114) 184 (109) 147 (80)
2287 (143) 1106 (143) 1261 (154) 2281 (158) 1041 (114) 1287 (206) 2291 (124) 1581 (296) 1279 (189) 2320 (169) 1479 (283) 1322 (106)
140 (100) 102 (69) 81 (77) 120 (65) 72 (64) 114 (117) 132 (68) 111 (68) 66 (38) 135 (77) 141 (101) 77 (42)
M5
1581 (503)
131 (78)
1462 (469)
160 (104)
1627 (512)
108 (90)
a Standard
deviation values are shown in parentheses.
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Average FFF According to Phonetic Context. The average FFF values for each CVt token across each subject group are listed in Table 2. The largest FFF was found among the untreated stutterers across nine of the 12 CVt tokens. The exceptions were /pat/, /bat/, and /sat/, which showed smaller FFF compared to the nonstuttering control group. The smallest FFF was found among the treated stutterers across nine of the 12 CVt tokens. The exceptions to this pattern were the /pit/, /sut/, and /zut/ tokens which showed the smallest FFF among the control group. A series of alpha-adjusted ANOVAs were performed to determine whether the FFF of each CVt token significantly differed across the three subject groups. The main effect was significant for /put/ [F (2,42) 5 5.06, p , 0.05)], /sit/ [F (2,42) 5 4.80, p , 0.05], and /zat/ [F (2,42) 5 4.91, p , 0.05]. Post-hoc Scheffe t tests identified a significantly smaller FFF (two-tailed, p , 0.05) among the treated stutterers compared to the untreated stutterers for production of the /put, sit, zat/ tokens. In addition, treated stutterers displayed a smaller FFF compared to the control group for production of /zat/ (two-tailed, p , 0.05). Overall FFF. The overall FFF results for each group are listed in Table 2. The group results were calculated by collapsing the FFF values for each CVt token produced by each subject within a group. In general, the pattern of FFF found for the individual CVt tokens was evident for the overall group data. The smallest overall FFF was found among the treated stutterers (M 5 108.0 Hz), followed by the control group (M 5 131.4 Hz). The largest overall FFF was found for the untreated stutterers (M 5 160.3 Hz). The overall variability in FFF was roughly similar between the treated stutterers (Sd 5 80.1 Hz) and control group (Sd 5 78.9). The largest overall variability in FFF was found for the untreated stutterers (Sd 5 104.5). A one-way ANOVA was performed on the group data to determine whether overall FFF significantly differed across the three subject groups. The main effect was significant [F (2,432) 5 12.53, p , 0.05]. Post-hoc Sheffe t tests identified a significantly larger overall FFF among the untreated stutterers compared to the control group (two-tailed, p , 0.05), and compared to the treated stutterers (twotailed, p , 0.05). There were no significant differences in overall FFF between the control group and the treated stutterers.
Vowel Durations According to Phonetic Context. The average vowel duration values for each CVt token across each subject group are listed in Table 3. Across the 12 CVt tokens, the shortest vowel durations were consistently noted for the control group. The longest vowel durations were observed for the group of treated stutterers. The only exception to this pattern was identified for the /pat/ token
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which was slightly longer for the untreated stutterers. A series of alpha-adjusted ANOVAs were performed to determine whether the average vowel duration of each CVt token significantly differed across the three subject groups. Although a general pattern of vowel durations was observed across the groups, results of the ANOVA testing failed to find significant differences for any of the CVt tokens. Overall Durations. The overall vowel durations for each group are listed in Table 3. The shortest vowel durations were observed for the control group (M 5 173 ms), followed by the group of untreated stutterers (M 5 203 ms). The longest vowel durations were found for the group of treated stutterers (M 5 217 ms).
DISCUSSION The above results and ensuing interpretations should be viewed with caution. The number of subjects and speech tokens considered in the analysis were small which contributed to an FFF measurement error approximating the effect size. Because of the small database, sufficient statistical power to detect group differences could not be fully ensured (Kirk, 1982). In light of these limitations, group differences were noted in the stability of F2. Untreated stutterers consistently showed the largest FFF for production of a majority of the CVt tokens, while the treated stutterers showed the smallest FFF across tokens.
Table 3. Average Vowel Duration (in msec) of Each CVt Token for the Control Group (C), Untreated Stuttering Subjects (U), and Treated Stuttering Subjects (T) Vowel Duration Token
C-Group
U-Group
T-Group
/pit/ /put/ /pat/ /bit/ /but/ /bat/ /sit/ /sut/ /sat/ /zit/ /zut/ /zat/
144 (27) 152 (22) 162 (16) 176 (32) 174 (26) 196 (33) 152 (21) 156 (30) 186 (41) 192 (38) 196 (35) 198 (43)
182 (45) 167 (30) 197 (37) 212 (63) 210 (37) 212 (20) 195 (44) 200 (100) 207 (29) 212 (18) 190 (42) 217 (41)
186 (69) 194 (58) 196 (53) 236 (69) 230 (81) 230 (35) 202 (73) 202 (60) 212 (47) 228 (70) 244 (68) 246 (39)
M5
173 (34)
203 (49)
217 (59)
Standard deviations are shown in parentheses.
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The small FFF across the treated stutterers is most likely attributable to the effects of fluency-shaping therapy. Pre-therapy CVt samples were not obtained from these subjects which would have allowed for direct examination of treatment effects on FFF. Still, particular features of the fluency refresher program received by these subjects emphasized controlled speech rate, light articulatory contacts, and continuous phonation (Webster, 1975). It is interesting to note that in addition to demonstrating the smallest FFF, the group of treated stutterers also displayed the longest vowel durations and highest average F2 values. Taken as a whole, these findings would indicate a rather complex pattern of speech motor control associated with the maintenance of speech fluency among the treated stutterers. While the present study was concerned with evaluating vocal tract stability using the FFF measure, a comment is warranted regarding the possible clinical utility of this measure. Assuming FFF provides an inferential estimate of vocal tract stability (Gerratt, 1983), it may also serve as a sensitive measure of speech fluency. For example, consider the overall differences in FFF across the three subject groups. The FFF for the untreated stutterers was approximately 30 Hz larger compared to the nonstuttering control group, and over 50 Hz larger than the treated stutterers. In other words, the untreated stutterers demonstrated the most vocal tract instability in what were perceived to be fluent CVt productions. It is possible that the FFF measure was revealing of speech dysfluency which was not perceptually identifiable (cf., Armson & Kalinowski, 1994). An interesting test of the FFF measure would be to compare the FFF characteristics of perceptually dysfluent speech to perceptually fluent speech to note whether vocal tract stability varies as a function of perceived speech fluency. In conclusion, past research examining F2 transitions has shown that stutterers experience difficulty in transitioning from one speech sound to the next in CVC contexts (Robb & Blomgren, 1997; Yaruss & Conture, 1993). To the extent that FFF serves as a measure of vocal tract stability, the present findings indicate that disordered articulation is also manifest in the steady-state portion of vowels. Using refined methods of acoustic analysis such as FFF, it is becoming increasingly clear that the fluent speech of stutterers is more different than similar to that of normally fluent individuals. We wish to thank Drs. Jay Lerman and Robert Prosek who provided comments on early versions of this manuscript.
REFERENCES Armson, J. & Kalinowski, J. (1994). Interpreting results from the fluent speech paradigm in stuttering research: Difficulties in separating cause from effect. Journal of Speech and Hearing Research 37, 69–82.
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Gerratt, B. (1983). Formant frequency fluctuation as an index of motor steadiness in the vocal tract. Journal of Speech and Hearing Research 26, 297– 304. Hillenbrand, J., Getty, L., Clark, M., & Wheeler, K. (1995). Acoustic characteristics of American English vowels. Journal of the Acoustical Society of America 97, 3099–3111. Howell, P. & Vause, L. (1986). Acoustic analysis and perception of vowels in stuttered speech. Journal of the Acoustical Society of America 79, 1571– 1579. Johnson, W., Darley, D., & Spriestersbach, D. (1963). Diagnostic Methods in Speech Pathology. New York: Harper & Row. Kent, R. & Read, C. (1992). The Acoustic Analysis of Speech. San Diego, CA: Singular Publishing Inc. Kirk, R. (1982). Experimental Design: Procedures for the Behavioral Sciences (2nd Ed.). Belmont, CA: Brooks/Cole Publishing Co. Klich, R. & May, G. (1982). Spectrographic study of vowels in stutterers’ fluent speech. Journal of Speech and Hearing Research 25, 364–370. Metz, D., Onufrak, J., & Ogburn, S. (1979). An acoustical analysis of stutterers speech prior to and at the termination of therapy. Journal of Fluency Disorders 4, 249–254. Nearey, T. & Shammass, S. (1987). Formant transitions as partly distinctive invariant properties in the identification of stops. Canadian Acoustics 15, 17–24. Newman, P., Harris, R., & Hilton, L. (1989). Vocal jitter and shimmer in stuttering. Journal of Fluency Disorders 14, 87–95. Peterson, G. & Barney, H. (1952). Control methods used in a study of vowels. Journal of the Acoustical Society of America 24, 173–184. Prosek, R., Montgomery, A., Walden, B., & Hawkins, D. (1987). Formant frequencies of stuttered and fluent vowels. Journal of Speech and Hearing Research 30, 301–305. Robb, M. & Blomgren, M. (1997). Analysis of F2 transitions in the speech of stutterers and nonstutterers. Journal of Fluency Disorders 22, 1–16. Stevens, K. & House, A. (1955). Development of a description of vowel articulation. Journal of the Acoustical Society of America 27, 484–493. Stromsta, C. (1965). A spectrographic study of dysfluencies labeled as stuttering by parents. De Therapia Vocis et Loquelae. Proceedings of the 13th Congress of the International Association of Logopedics and Phoniatrics, Vienna, 1, 317–320. Stromsta, C. (1986). Elements of Stuttering. Oshtemo, MI: Atsmonts Publishing.
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Webster, R. (1975). The precision fluency shaping program: Speech reconstruction for stutterers. Roanoke, VA: Communications Development Corp. Yaruss, J. & Conture, E. (1993). F2 transition during sound/syllable repetitions of children who stutter and predictions of stuttering chronicity. Journal of Speech and Hearing Research 36, 883–896. Zimmermann, G. (1980). Articulatory dynamics of fluent utterances of stutterers and non-stutterers. Journal of Speech and Hearing Research 23, 95–107.