Speech act recognition in Spanish speakers

Journal of Pragmatics 141 (2019) 44e56

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Journal of Pragmatics journal homepage: www.elsevier.com/locate/pragma

Speech act recognition in Spanish speakers
squez-Upegui b, T. Holtgraves c, M. Giordano a, * G.L. Licea-Haquet a, E.P. Vela a
noma de M
Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Auto exico, Boulevard Juriquilla 3001, Juriquilla, Qro, 76230, Mexico b
noma de Quer
Facultad de Lenguas y Letras, Universidad Auto etaro, Campus Aeropuerto, Quer
etaro, M
exico, Anilllo Vial Fray Junipero Serra S/N, Santiago de Quer
etaro, Qro, 76140, Mexico c Department of Psychological Science, Ball State University, Muncie, IN, 47306, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Received 4 April 2018 Received in revised form 13 December 2018 Accepted 14 December 2018

Language comprehension involves the recognition of speech acts. The term speech act refers to what a speaker intends to accomplish when saying something. Holtgraves (2008) demonstrated that English speakers can automatically recognize speech acts, and proposes that this allows an efficient (good-enough) processing of conversation turns. Other studies have found that speech act recognition requires cognitive process like executive functions, theory of mind, and empathy. However, there are few studies that have empirically investigated which are the cognitive functions needed for speech act recognition in healthy adults. The aim of this work was to study if Spanish speakers automatically recognize speech acts, and if this recognition is related to intellectual ability and other cognitive functions. We examined this question using the methods described by Holtgraves (2005, 2008). First, we translated and adapted the scenarios, and selected those that were better understood. Then, we designed two experiments to test the automatic recognition of speech acts. Participants underwent a battery of psychometric and cognitive tests. We found significant differences in reaction times between control and experimental scenarios, which indicates that Spanish speakers automatically recognize speech acts. A measure of intellectual ability, as well as the ability to reason about mental states of others, predicted in part the ability to recognize speech acts. © 2018 Elsevier B.V. All rights reserved.

Keywords: Illocutionary force Speech act theory Conversation comprehension

1. Introduction Language comprehension involves not only understanding the meaning of words and the relations between them, but also the contextualization of discourse. Theories about pragmatic language propose that speech comprehension involves the recognition of the speaker's intentions. One important approach to the study of speaker's intentions is the Speech Act Theory, according to which conversational utterances involve the execution of multiple acts (promise, order, or suggest). In an attempt to understand utterances in interaction, John Austin (1962) in his Speech Act Theory explained speech acts as communicative acts in which speakers perform actions via utterances in specific contexts. He proposed saying something is always doing something and that any speech act can be divided into three acts: locutionary, illocutionary, and perlocutionary (Domaneschi et al., 2017; Lee, 2016; Oishi, 2006).

* Corresponding author. E-mail address: [email protected] (M. Giordano). https://doi.org/10.1016/j.pragma.2018.12.013 0378-2166/© 2018 Elsevier B.V. All rights reserved.

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The locutionary act is the actual production of an utterance, the illocutionary act is the intention of the speaker, the action performed by uttering a certain sentence. It is characterized by the illocutionary force, or the intended socially valid verbal action. The same proposition can convey different illocutionary forces and perform different actions in particular contexts, this is because locutionary and illocutionary acts are independent. The perlocutionary act is the actual effect produced by a speech act, like persuading, convincing, scaring, and getting someone to do or to realize something (Domaneschi et al., 2017; Lee, 2016; Oishi, 2006). John Searle extended Austin's concept of speech acts and elaborated on the Speech Act Theory by identifying the conditions that are necessary for the realization of speech acts. For example, to promise, the speaker needs sincerity and intentionality; to declare the marital union of two partners, a priest or a judge must be present. Hence, the successful performance of a speech act depends on whether the constituent conditions are fulfilled and realized in a contextually appropriate manner. Searle also proposed an illocutionary acts classification that includes: assertive acts, by which the speaker says how something is; directive acts, by which the speaker tries to get the hearer to perform some future action, such as requesting and warning; commissive acts, by which the speaker commits to some future course of action, such as pledging and promising; expressive acts, which allow the speaker to articulate his or her psychological state of mind about some prior action, such as apologizing and thanking; and declarative acts, which require non-linguist institutions, such as christening or sentencing (Lee, 2016; Searle, 1976). There is some psychological evidence that people do extract speech act information online. Using a recognition probe task and lexical decision task, Holtgraves (2008) addressed whether the comprehension of a sentence like “Don't forget to go to your dentist” (an “implicit speech act”) entails automatic activation of the speech act performed (reminding). Using a behavioral task that included the presentation of scenarios followed by a control utterance or a speech act utterance, and measuring errors and reaction time, he found that the recognition of such speech acts is automatic. This was true for both written and spoken utterances, and thus he concluded that speech acts capture in a single word the action a speaker is performing with an utterance, and this allows for efficient processing of conversation turns. Si Liu (2011) adapted Holtgraves' methods and tested if utterance comprehension involved speech act recognition when the language in use is Chinese. Participants were asked whether the probe word had literally appeared in the target utterance. He found that the reaction time difference between the experimental version (speech act) and the control version was not significant. However, significantly more errors were made in the experimental trials, suggesting that the speech act probes were more difficult to reject. The conclusion of the study was that illocutionary force recognition is involved in speech act interpretation. Therefore, when a speaker tries to get the hearer to understand her, she must be trying to get her illocutionary act to be recognized (Searle and Vanderveken, 1985). To recognize speech acts, as well as the richness of meanings that arise whenever language is used to communicate, it is necessary to consider not only phonetics, semantics, and syntax, but these broader, inferred meanings that comprise the pragmatic dimension of language and that are a product of the linguistic units chosen and the physical and social context in which they occur. Thus, the ability to communicate relies not only upon an intact language system, but also upon knowledge of the specific communicative context, knowledge about the co-conversant(s), as well as general knowledge of the world. It relies upon “higher order” abilities whereby numerous cognitive systems interact so that knowledge of context and language can combine to generate novel inferences specific to each communicative act (Cummings, 2017; Martin and McDonald, 2003). What we know about the role of cognitive functions in pragmatic competence is generally based on insights derived from cognitive impairments in patients. The two main cognitive functions that have been related to pragmatic competence are: Theory of Mind (TOM) and the Executive Functions (EF) system. TOM refers to the ability to form representations of other people's mental states and to use these representations to understand, predict, and judge utterances and behavior. Indeed, this component of social inference ability is considered pivotal to one's ability to engage in effective communication. Although there is good evidence for TOM deficits associated with communication difficulties in people with autism and right hemisphere damage, the direction of this relationship is unclear. Whilst some claim that TOM is a necessary precursor to developing social communication skills, others argue that it is experience with social communication that actually leads to proficient TOM reasoning (Cummings, 2017; Martin and McDonald, 2003). The EF system is argued to drive motivated adaptive behavior, and allows healthy individuals to respond to novel and challenging tasks. Frontal lobe mediated abilities are also thought to include processes such as concept formation and abstract and inferential reasoning. The EF system coordinates behavior, enabling a person to use their cognitive abilities in various situations in a flexible manner. Considering that conversation rules change with the context in which each particular conversation occurs, it would appear that an intact EF system is necessary for normal individuals to engage in motivated, adaptive, and effective communication (Cummings, 2017; Martin and McDonald, 2003). Another question widely acknowledged is that people from different cultures communicate differently. According to the Sapir-Whorf hypothesis, the language we speak, particularly the structure of that language, determines how we perceive and experience the world around us (Ji et al., 2004; M. Liu, 2016; Perlovsky, 2009). There is also evidence that communication style, which is the way people communicate verbally and nonverbally with others, combines both language and nonverbal cues. These “meta-messages” that dictate how listeners receive and interpret verbal messages are shaped and reshaped by shared cultural values, worldviews, norms, and thinking styles of the cultural group to which they belong (Hall and Hall, 2001; M. Liu, 2016; Nishimura et al., 2008).

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One theoretical perspective that may be useful for understanding cultural variations in communication styles is the differentiation between high-context and low-context communication proposed by Edward Hall (1976). In high-context cultures, communication style is influenced by the closeness of human relationships, well-structured social hierarchy, and strong behavioral norms. Internal meaning is usually embedded deeply in the information, so not everything is explicitly stated in writing or when spoken. For that reason, the listener is expected to be able to “read between the lines,” to understand the unsaid, thanks to his or her background knowledge. In high-context cultures, communication is indirect and ambiguous. Greater confidence is placed on the nonverbal aspects of communication than on the verbal aspects. In contrast, in lowcontext cultures meanings are explicitly stated through language. People communicating usually expect explanations when something remains unclear. Most information is expected to be in the transmitted message to make up for what is missing in the context (both internal and external). This type of culture is characterized by direct and linear communication and by the constant use of words. Communication is direct, precise, dramatic, open, and based on feelings or true intentions (Hall and Hall, 2001; Nishimura et al., 2008). Communication styles become major sources of misunderstanding, frustration, and conflict in intercultural communication. The United States is a low-context culture, whereas China is a high-context culture. This difference in communication styles may contribute to how speech acts are recognized in an utterance, as the studies of Holtgraves (2008) and Liu (2011) show. Latin America, like China, is a high-context culture, so we expected to obtain results similar to those of Liu (2011). To date, there are no studies of speech act recognition in Latin America or Mexico that can determine the role of speech acts in utterance comprehension. In addition, there are few empirical studies that have evaluated the relation between this process and other cognitive functions in healthy people. The aims of this study, then, were to evaluate how easily Spanish speakers recognize speech acts, and whether this recognition is an automatic process that is related to intellectual ability and other cognitive functions. 2. Methods All participants were neurologically intact, native Spanish speakers between the ages of 18 and 33, all of them were either studying for an undergraduate or graduate degree, or had already obtained a bachelor's degree. Participants were recruited from nearby universities and research institutes, and gave their written informed consent to take part in the experimental procedures, which followed national and international guidelines and were approved by the Ethics in Research Committee of the Instituto de Neurobiología-UNAM. The study involved four different experiments, each one in a different sample of participants, and a final regression analysis to identify which cognitive measures are related to speech act recognition. The first experiment describes the selection of scenarios with an identification task, the second experiment replicated the exact task described in Holtgraves (2008), the third experiment presents the results of a modified version of the online speech act activation task, and the fourth experiment presents the results of a lexical decision task to probe if speech acts recognition is an automatic process. The last part of the paper presents the results of a regression analysis with cognitive measures, to identify which of these are related to speech act recognition. The methodological details of each experiment and analysis are given in the following section. 2.1. Experiment 1. Identification task 2.1.1. Participants Seventy-six participants between the ages of 18 and 33, with a mean age of 25.6, answered two booklets (booklet A ¼ 40, 18 females; booklet B ¼ 36, 19 females). 2.1.1.1. Materials and procedure. We used forty-eight speech act scenarios. Twenty-seven speech act scenarios were translated and adapted to Spanish from (Holtgraves, 2005, 2008). The remaining twenty-one were created with the same structure. Of the forty-eight speech act scenarios, twelve were directives, sixteen assertives, ten commissives and six expressives. Each scenario contained a brief, three-to-five sentence description of a situation. The last sentence was a speech act, and participants were asked to write a single word that indicated the specific action that they believed the speaker was performing with the last remark. Two experimental booklets were constructed, each containing the instructions, two examples, and twenty-two scenarios. Participants worked through the booklets at their own pace with an approximate mean completion time of 25 min. The goal of this task was to select the speech act scenarios that were best identified by Spanish speakers. For each speech act scenario, the percentage of participants who identified the intended speech act was tabulated. Then, the scenarios for which at least 55% of participants provided the correct speech act were included in the subsequent phase as critical trials. The remaining scenarios were used as filler trials. Descriptive statistics were calculated, and comparisons between genders and types of speech acts were done using parametric tests (paired samples t-tests, analysis of variance with repeated measures). Multiple linear regression analyses were used to test if scores in cognitive tests predicted correct responses or reaction times (IBM™ SPSS™, v. 24). Data is presented as mean ± standard deviation, unless otherwise noted.

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2.1.2. Results We obtained the percentage of participants who identified the intended speech act. Twenty-six speech acts were identified by more than 55% of the participants, nine of these were directives, eight assertives, six commissives and three expressives. Those scenarios were selected for the next phase of the study (Fig. 1). The speech acts selected were invite, warn, encourage, beg, ask, correct, introduce, remind, blame, congratulate, apologize, offer, promise, threaten, warn, invite, accuse, lie, thank, and forgive. We examined if there were differences in the percentage of correct speech act identification between males and females, and across the different types of illocutionary acts. Commissives had a mean of 44.52 ± 37.57% in males and 42.35 ± 35.66% in females; expressives had a mean of 56.12 ± 23.58% in males and 54.42 ± 27.48% in females; assertives had a mean of 51.72 ± 32.56% in males and 55.68 ± 30.33% in females; and directives had a mean of 67.69 ± 21% in males and 67.28 ± 18.73% in females. We did not find any significant differences in the percentage of correct identification between genders or between types of illocutionary acts (Fig. 2).

2.2. Experiment 2: online speech act activation task 2.2.1. Participants Sixteen participants (15 females) between the ages of 18 and 30, with a mean age of 21.9 years, completed this task. 2.2.2. Materials and procedure The experiment was programed on PsychoPy2 software (Peirce, 2007). Participants first read detailed instructions on the task and then engaged in the practice trials. Participants pushed the space bar to begin a trial and the first scenario appeared on the screen. Participants read the scenarios at their own pace and pushed the space bar to proceed through the material. After indicating comprehension of the last remark in a scenario, a 500-Hz tone sounded for 100 Ms. One second later, a probe word appeared in the middle of the screen. Participants were instructed to indicate, as quickly as possible, if the word had been literally present in the last remark they read. They were instructed to push the key marked YES (M key) if they believed it described the action, and the key marked NO (Z key) if they believed it did not describe the action. An example of each condition is shown in Table 1. Following the method described by Holtgraves (2008), we designed two versions of the task. Each version contained the same instructions, six practice trials in which the program provided feedback, and 48 scenarios (24 critical trials and 24 filler trials). The critical trials were divided as follows: 12 speech acts (experimental) in which the probe word represented the act performed in the last utterance of the scenario; and 12 control trials that shared as many words as possible with the speech act versions, but in the final utterance it did not perform the speech act that the probe word described. This was accomplished by switching the tense of the utterance, switching the sentence participant, or negating the speech act. In both cases, the probe word had not literally been present in the final remark, and hence the correct response was “NO.” The remaining 24 were filler trials almost were identical to the critical trials, except that the probe word following each scenario had always appeared in the last remark, and hence the correct response was “YES.” These trials were included to prevent participants from developing an expectation that the probe word was never present in the final remark. The two versions were mirror images of each other. If the control version of a scenario appeared in one set, then the speech act version of that scenario appeared in the other set. The twenty-four speech act scenarios were selected from Experiment 1, nine were directives, eight assertives, two commissives and five expressives. The same set of speech act scenarios was used for experiments 3 and 4. Holtgraves (2008) proposed that if comprehension entails speech act activation, then when the probe word represents the speech act just performed, the participants’ ability to verify that the word had not been literally present should be hindered and the activation of the speech act term should interfere with performance in this task. Thus, participants are expected to make more mistakes and take longer to answer speech act scenarios compared to control scenarios. Holtgraves found that in native English speakers these predicted effects occurred for both error rates and reaction times, and he concluded that the comprehension of conversation utterances performing implicit speech acts entailed activation of the speech act performed with the utterance. The goal of this experiment was to examine if the same was true for native Spanish speakers. 2.2.3. Results For the analysis, we calculated the percentage of correct answers for each participant and the reaction times only for the correct trials. Only participants that understood and completed the task were included. We excluded four participants that obtained less than 30% percent of correct answers. No significant differences in the percentage of correct answers nor in the reaction times between experimental (speech act) and control trials were found using a Wilcoxon test, and a two-paired sample t-test respectively. Spanish speakers answered slightly better in experimental trials (93.18 ± 9.731%, Mdn ¼ 100, IQR ¼ 8.33) than in control trials (90.15 ± 7.282%, Mdn ¼ 91.66, IQR ¼ 16.67), and took less time to answer in experimental trials (1615 ± 665.8 ms, 95% CI [1167.35, 2061.98]) than in control trials (1891 ± 702.3 ms, 95% CI [1419.39, 2362.98]) (Fig. 3a and b).

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Claim Invite Warn Encourage Beg Ask Deny Justify Correct Introduce Remind Blame Guess Compliment Complain Congratulate Brag Apologize Offer Promise Reassure Threaten

Booklet A

Ask Warn Encourage Beg Invite Ask Introduce Guess Blame Deny Correct Remind Justify Accuse Lie Thank Congratulate Complain Forgive Congratulate Offer Reassure

Booklet B

0

10

20

30

40

50

60

70

80

90

100

Percentage of correct speech act identification Fig. 1. The graph shows the percentage of participants that correctly identified each speech act in each booklet. The speech acts that were correctly identified by 55% or more of the sample were used in the next phase of the study.

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a

80 60 40 20 0

100

% of correct answers

% of correct answers

100

Comissive Expressive Assertive

Directive

b

80 60 40 20 0

Male

100

% of correct answers

49

Female c

80 Directive Assertive Comissive Expressive

60 40 20 0

Male

Female

Fig. 2. The graphs show the percentage of participants that correctly identified each type of speech act (a), and the percentage of correct identification by males and females considering all types of speech acts (b). Graph (c) shows the percentage of correct identification by males and females of each type of speech act. Each bar shows the median (horizontal bar), interquartile range, 10th and 90th percentile, and outliers. No significant differences were found. The mean is represented with a cross.

2.3. Experiment 3 modified online speech act activation task We considered that the results in Experiment 1 could be due to differences in language structure between Spanish and English, and in the form and conjugations of verbs. In the experimental and control trials, the probe word was always a verb in the infinitive form, but in the filler trials since we were asking if the word was literally present in the last remark of the scenario, it was a conjugated verb. Thus, we decided to modify the original task in order to control the form of the verbs, and again compare against the results reported by Holtgraves (2008). To do this we changed the instruction, and instead of asking if the probe word was literally present in the last remark of the scenario, we asked if the verb was present in the last sentence;
(broke or kicked), in the filler trials, we used verbs in the infinitive and instead of using conjugated verbs, e.g., rompí or pateo form, e.g., romper or patear (to break or to kick). In that way, all probe words were verbs in the infinitive form (for an example, see Table 2). 2.3.1. Participants Forty-six participants (23 females) between the ages of 18 and 30, with a mean age of 23.3 years, completed the modified version of the task.

Table 1 Examples of target sentences for each condition used in online speech act activation task. Sentence

Word probe

Condition

No te Don't No te Don't No te Don't

Encourage Animar Encourage Animar Stop Detengas

Speech Act

detengas, tú puedes lograrlo. stop, you can do it. detengas, ella puede lograrlo. stop, she can do it. detengas, tú puedes lograrlo. stop, you can do it.

Control (NO) Filler (YES)

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90 60 30 0

b

2000

1000

0 Experimental Control Condition

120

Modification

Experimental Control Condition

*

c

d

4000

Reaction time (s)

% of correct answers

3000

a

Reaction time (s)

% of correct answers

120

90 60 30 0

Experimental Control Condition

% correct Reaction time (ms) % correct Reaction time (ms)

3000 2000 1000 0

Experimental Control Condition

Experimental 93.18 ± 9.731 1615 ± 665.8

Control 90.15 ± 7.282 1891 ± 702.3 Modification 81.75 ± 18.24 81.75 ± 12.38 2469 ± 1608 2058 ± 689.7 * Mean and standard desviation

Fig. 3. Online speech act activation task, and its modification. The graphs show the percentage of correct responses and reaction time (ms) for the online speech act activation task (a, b) and its modified version (c, d). No differences were found in the original version of the identification task. In the modified version of the task we found a significant difference between control and experimental scenarios in reaction times (t (41) ¼ 2.22, p<0.05, 95% CI [37.12, 785.89] of the difference between the mean).

Table 2 Examples of target sentences for each condition used in the modified online speech act activation task. Sentence

Word probe

Condition

No te Don't No te Don't No te Don't

Encourage Animar Encourage Animar Stop Detener

Speech Act

detengas, tú puedes lograrlo. stop, you can do it. detengas, ella puede lograrlo. stop, she can do it. detengas, tú puedes lograrlo. stop, you can do it.

Control (NO) Filler (YES)

2.3.2. Results As in the previous version, we counted the percentage of correct answers for each participant and the reaction times only for the correct trials and calculated a paired two samples t-test. We excluded four participants that obtained less than 30% of correct answers. We did not find any statistically significant differences in the percentage of correct responses between experimental (81.75 ± 18.24%, Mdn ¼ 83.33, IQR ¼ 16.67) and control trials (81.75 ± 12.38%, Mdn ¼ 83.33, IQR ¼ 16.67), but with the

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modification we found significant differences (t(41) ¼ 2.22, p < 0.05) in reaction times between experimental and control scenarios. Participants took significantly longer to answer experimental trials (2469 ± 1608 ms, 95% CI [1968, 2970]) than control trials (2058 ± 689.70 ms, 95% CI [1843, 2273]) (see Fig. 3c and d).

2.4. Experiment 4: Lexical decision task 2.4.1. Participants Sixteen participants (11 females) completed the task. Ages ranged from 18 to 30, with a mean age of 23.1 years. 2.4.2. Materials and procedure Experiment 2 was similar to Experiment 1, with a few exceptions. After indicating comprehension of the last remark, a fixation point appeared on the screen for either 250 ms (short delay) or 2000 ms (long delay). During this delay a 500Hz tone sounded for 100 ms, and then the target appeared in the middle of the screen. An equal number of speech acts and control versions appeared in both the short and long delay trials. The experiment was programmed using the same scenarios, but in the 24 filler trials of Experiment 2, the target was always a non-word. Participants were instructed to indicate, as quickly as possible, if the target was a word. The targets for the 24 critical trials were always words and required “Yes” responses, and the targets for the 24 filler trials were always non-words and required “No” responses.
, The non-word letter strings presented in the filler trials were created by reversing two letters of real words (e.g., tapeo gisue, ropmí) describing the speech act performed with the prior utterance. Participants were to select the key marked YES (M key) if they judged the target to be a word, and the key marked NO (Z key) if they judged the target to be a nonword. Holtgraves (2008) proposed that the results of Experiment 1 could be due to some type of context-checking procedure. Thus, it was important to demonstrate an online effect with more than one task, ideally tasks in which the predicted effects diverged. The first purpose of this experiment was to replicate the results of Experiment 1 using a different task and to examine evidence for speech act activation by varying the stimulus onset asynchrony (SOA). In this experiment, if comprehension of an implicit speech act entails speech act activation, then participants should be significantly faster at this task when the target represents the performed speech act than when it does not, the opposite of what was expected in Experiment. The second purpose of this experiment was to examine the time course of speech act activation. If speech act activation is an automatic rather than controlled process, then activation must occur very quickly. Although there are no exact cut-offs, priming effects that occur at SOAs longer than 1500 ms are generally taken as reflecting a controlled process. Those occurring at 250 ms or less are viewed as automatic processes (Groot, 1984; Holtgraves, 2008; Posner and Snyder, 1975). We chose delays of 2000 ms (long delay) and 250 ms (short delay) as shown in Holtgraves (2008). We expected speech act activation (i.e., a priming effect) to occur for the short delay but not for the long delay. 2.4.3. Results Only error-free trials were included in the analyses of the lexical decision reaction times. We excluded four participants from the analyses because they had less than 30% correct answers. In trials with short delay, for the experimental condition there were 94.87 ± 18.49% correct answers (Mdn ¼ 100, IQR ¼ 0) and for the control condition there were 92.31 ± 16.12% correct answers (Mdn ¼ 100, IQR ¼ 8). The reaction time for the experimental condition had a mean of 1416.18 ± 880 ms (95% CI [884.37, 1947.99]) and the control had a mean of 1766.14 ± 1107.22 ms (95% CI [1037.05, 2375.23]). In trials with long delay, the percentage of correct answers for the experimental condition had a mean of 96.15 ± 13.86% (Mdn ¼ 100, IQR ¼ 0) and for the control a mean of 94.87 ± 10.50% (Mdn ¼ 100, IQR ¼ 8); whereas the reaction time in the experimental condition had a mean of 1233.74 ± 417.72 ms (95% CI [ 931.31, 1486.16]) and the control had a mean of 1368.43 ± 444.14 ms (95% CI [1100.03, 1636.82]). Although in the experimental (speech act) trials participants tended to discriminate faster if the target was a word than in control trials, we did not find any statistically significant differences in both short and long delay trials and we observed no priming effect using a Friedman test. Hence, we cannot conclude that Spanish speakers identify speech acts in an automatic way as English speakers do. 2.5. Cognitive tests To investigate which cognitive processes may be involved in speech act comprehension, we applied a battery of tests to 28 participants in the modified online speech act activation task. We evaluated verbal comprehension and perceptual reasoning using the Wechsler Adult Intelligence Scale, WAIS IV (Wechsler, 2012). Executive functions (inhibitory control, working
gica de Funciones Ejememory, verbal fluency, and mental flexibility) were evaluated by means of the Batería Neuropsicolo
bulos Frontales (BANFE) (Flores et al., 2014). To evaluate Theory of Mind (TOM) we used two tests: Read the Mind in cutivas y Lo the Eyes Test (RMET) (Baron-Cohen et al., 1997) and the Short Story Task (Dodell-Feder et al., 2013). The first test measures the emotional component and the second measures the cognitive component of TOM. We used the Interpersonal Reactivity Index (IRI) (Davis, 1980) to evaluate empathy.

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Testing was done individually in a well-lit room, free of noise and distractors, and in a different session from the scanning session. Tests were applied using three different orders that were counterbalanced to avoid a fatigue effect. Mean time of application was 3 h. Participants were informed that they could take a break if needed (mean scores in Table 3).

Table 3 Scores from tests to evaluate verbal comprehension, perceptual reasoning, executive functions, Theory of Mind, and empathy (mean and standard deviation; n ¼ 28).

WAIS

Executive functions BANFE

Theory of Mind (emotional) Theory of Mind (cognitive)

Empathy

Test

Score

Verbal comprehension index Perceptual reasoning index General ability index Inhibitory control Working memory Verbal fluency Mental flexibility Read the Mind in the Eyes (RMET) Short Story Task (spontaneous inference) Short Story Task (comprehension) Short Story Task (mental state reasoning) Perspective taking Fantasy Empathic concern Personal distress

106.39 ± 10.93 106.93 ± 10.12 107.10 ± 10.40 180.5 ± 6.69 58.03 ± 4.02 25 ± 6.12 64.43 ± 11.67 25.89 ± 4.16 0.10 ± 0.31 7.43 ± 1.69 6.32 ± 2.80 18.57 ± 5.05 13.89 ± 5.85 19.03 ± 6.17 11.07 ± 6.17

2.5.1. Results Regarding performance in the modified online speech act activation task, we used multiple regression analysis and found that about 20% of the variance in the reaction times for experimental scenarios was explained by the general ability index (WAIS) and the explicit mental state reasoning (Short Story Task) [general ability index, F (1, 26) ¼ 7.932, p < 0.05, R2 ¼ 0.234, R2adjusted ¼ 0.204, Beta ¼ 0.483; explicit mental state reasoning, F (1, 25) ¼ 7.944, p < 0.05, R2 ¼ 0.241, R2adjusted ¼ 0.211, Beta ¼ 0.491] (Fig. 4).

Fig. 4. The graphs show the relation between accuracy in the online speech act activation task, and the scores in cognitive tests. The reaction time to answer experimental scenarios is predicted by the general ability index of the WAIS (p<0.01) (a) and the explicit mental state reasoning scores of the Short Story Task (p<0.01) (b).

3. Discussion The purpose of this study was to explore how native Spanish speakers recognize speech acts, and if there are specific cognitive functions related to this process. Speech act theory, being rooted in Western European and Anglo-American traditions and modes of thinking, may not hold for all languages and cultures (Senft, 2014), thus the importance of evaluating its relevance for the Latin American culture. The present study demonstrates that native Spanish speakers recognize the illocutionary force of speech acts in utterances. In the identification task, we identified 26 speech act verbs in scenarios that were recognized by more than 55% of the participants. We compared the percentage rate of speech act identification between genders and types of speech acts, and found no differences between genders. Similarly, we did not find differences in identification rates across the types of speech acts. This result could indicate that all types of speech acts are easily recognized by native speakers of a natural language.

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Alternatively, it may indicate that Searle's speech act typology may not reflect the way people categorize speech acts. In support of the latter, Holtgraves (2005) and Liu (2011) studied the way people classified speech acts in their respective languages (English and Chinese), and both found that this classification was not consistent with Searle's scheme. Instead, they found that people tended to classify speech acts in terms of interpersonal implications (positive, neutral, and negative). In the online speech act activation task, we expected participants to make more mistakes and take longer answering speech act scenarios than control scenarios because when the probe word represents the speech act just performed, the activation of the speech act term should interfere with performance in this task, as Holtgraves (2008) reported. However, this did not occur; we did not find differences in percentage of correct answers or in reaction times. We considered that this result could be due to language differences. English probe words were always verbs in the infinitive form (Holtgraves, 2008), while Spanish probe words were conjugated verbs in the filler trials, since the instruction was to indicate if the word literally appeared in the scenario. Therefore, we modified the task and changed the instructions, asking the participants to indicate if the verb had appeared in the scenario. We also changed the probe words to verbs in the infinitive form. With this modification we found significantly longer reaction times in experimental trials compared to control trials, thus replicating Holtgraves' (2008) findings. It is possible that the instruction to indicate if the word had been present interfered with the identification of the speech act, because in some trials the participants could indeed find the exact word; hence, they were not interpreting the illocutionary force of the statements but rather looking for a word. Liu (2011) employed the same paradigm used in this study and tested a sample of native Chinese speakers, but did not find significant differences in reaction times. However, similar to Holtgraves (2008) he found a significantly greater number of errors in the experimental trials and concluded that even if the interference effect was not reflected in reaction times, illocutionary force recognition was involved in speech comprehension. In this study, we did not find significant differences in the percentage of correct answers, but we found differences in reaction times that reflect the automatic role of speech act recognition during the task. The purpose of the lexical decision task was to investigate the priming effects of speech acts and to corroborate the results from the online speech act activation task. Considering the theory of attention proposed by Posner and Snyder (1975), which suggests that there are two types of processing (automatic, that is enacted very rapidly; and attentional, that is relatively time-consuming), this task was designed with two SOAs (250 and 1500 ms). Given that speech act priming is an automatic process, we expected it to facilitate responses with a short delay. We found a 30% reduction in reaction times between experimental (speech acts) and control versions in short delay trials. Compared to the 10% reduction we found in long delay trials, this result suggests that speech acts had a priming effect, but it did not reach statistical significance likely due to the number of participants. Interestingly, mean reaction times were longer in this study than those reported for English and Chinese speakers. Spanish speakers' reaction time for the modified online speech act activation task for speech acts was 2469 ms on average, while for English speakers it was 911.8 ms and for Chinese speakers it was 848.3 ms. Spanish speakers also had longer reaction times for control trials, with an average of 2058 ms, while for English speakers it was 882.2 ms and for Chinese speakers, 842.61 ms. For the lexical decision task, Spanish speakers’ mean reaction time for short delay trials was 1199.88 ms and for English speakers it was of 818.6 ms. It is possible that due to these slow rates of response in Spanish speakers, we could not detect the priming effect of speech act recognition. There is evidence that speech act processing begins from the moment people read or listen to the first word. Gisladottir, Chwilla, Schriefers, and Levinson (2012) investigated participants’ competence in categorizing speech acts in sentences and explored the time-course of speech act inferencing using a self-paced reading paradigm. Their results demonstrate that participants can categorize speech acts with very high accuracy, based on limited context and without any prosodic information. Furthermore, the results showed that a sentence is processed differently depending on the speech act it performs, and reading times differ from the first word. These results indicate that participants are very good at “getting” speech acts. Gisladottir, Chwilla, and Levinson (2015) investigated the time-course of auditory speech act recognition in actionunderspecified utterances and explored how sequential context impacts this process. They recorded event-related potentials (ERPs) while participants listened to spoken dialogues and performed an action categorization task. The ERP results showed an early effect of action type, reflected by frontal positivities as early as 200 ms after target utterance onset. This indicates that speech act recognition begins early when the utterance has only been partially processed. The authors concluded that listeners can recognize the action before they listen to the final word through predictions at the speech act level, thus demonstrating that sentence comprehension in conversational contexts crucially involves recognition of verbal action which begins very early on. These findings that speech act recognition begins even before the speech act is entirely said or listened to, suggest that reaction times in the interference and priming paradigms used in this work may reflect a working memory process in addition to the automatic interpretation of the utterance. Liu (2011) made an off-line experiment in which people read 14 scenarios and then were asked to select, from a list of 28 verbs, the speech acts preformed in the scenarios they had read. His findings demonstrated that the participants in this memory task would select the 14 speech act verbs that characterized the target utterances that they had read earlier, and that they would ignore the interfering verbs that had not been associated with the performed speech acts. In other words, when people interpreted an utterance, they were sensitive to the illocutionary force of the speech act. In addition to involving memory, speech act recognition likely involves other cognitive functions. Studies in populations with neurological disorders suggest that EF executive functions and TOM may play a role (Holtgraves and Giordano, 2017). In

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this study, we found that scores in the general ability index and in the explicit mental state reasoning test explain part of the variability in experimental reaction times. The general ability index is an optional index score for the WAIS-IV derived from the core verbal comprehension and perceptual reasoning subtests. It provides an estimate of general intellectual ability, with reduced emphasis on working memory and processing speed relative to the Full-Scale Intelligence Quotient. Theoretically, the general ability index represents an individual's overall cognitive ability (Wechsler, 2012). On the other hand, explicit mental state reasoning questions in the Short Story Task evaluate cognitive TOM through the accuracy of the mental state inference, number of character perspectives/emotions considered (i.e., second-order inferences generally received more points than first-order inferences), and understanding of non-verbal/indirect communications (e.g., sarcasm and body language) that participants can make after reading a story (Dodell-Feder et al., 2013).
s-Roqueta and Katsos (2017) proposed a distinction between two types of pragmatic abilities: linguisticAndre pragmatics, which refers to cases of pragmatics where structural language and competence with pragmatic norms are enough to perform successfully in a task; and social-pragmatics, which refers to cases where in addition to structural language and pragmatics, people need competence with TOM, and specifically the ability to represent other people's intentions, desires, and beliefs. This study supports the view that recognition of speech acts requires both types of pragmatic abilities, since we found that participants with high scores in the general cognitive functions domain (general ability index) and in a cognitive TOM measure of the Short Story Task tended to answer the experimental scenarios faster than those with low scores in these tests. One of the central issues in the study of speech acts in general is the question of universality. To what extent is it possible to reveal basic pragmatic features for given speech acts in any natural language? Cross-linguistic research can provide a better understanding of how human communicative interaction is carried out via linguistic realization patterns and describe similarities and differences in the ways in which such interactions are carried out under similar circumstances across languages or cultures. In a series of studies, Blum-Kulka and Olshtain (1984) investigated differences in two specific speech acts (request and apologize) across eight languages or varieties (Australian English, American English, British English, Canadian French, Danish, German, Hebrew, and Russian). They collected data from both native and non-native speakers and found that diversity of speech act patterns can come from intracultural variability resulting from situational and social parameters within the same culture (e.g., relative power, distance, and degree of imposition); cross-cultural variability, resulting from the different roles that social and situational parameters play in different cultures; and individual variability related to diversity of choices ensuing from personal factors such as age, sex, and level of linguistic competence (specifically relevant for second language learners). Also, speech act patterns can be influenced by sociocultural level and by the pragmatic force. Sociocultural level can constrain performance because the social and cultural norms may affect the speaker's decision to perform or not a given speech act; and it can also constrain performance, affecting the way the speaker chooses to realize the act. Pragmatic force involves the relationship between intention, the range of available linguistic forms, the choice of a strategy, and its realization in a certain grammatical and lexical form (Blum-kulka, 1983; Blum-Kulka, 1982; Blum-Kulka and Olshtain, 1984; Olshtain and Blum-Kulka, 1985). Those studies provided the methodological foundation for other comparative studies in speech act performance between cultures. For example, Wierzbicka (1985) studied differences in speech acts between English and Polish speakers and found that English, as compared to Polish, places heavy restrictions on the use of the imperative and makes extensive use of interrogative and conditional forms. The conclusions of this study were that linguistic differences may be associated with cultural differences such as spontaneity, directness, intimacy, and affection vs. indirectness, distance, tolerance, and antidogmatism. Gallaher (2014), on the other hand, investigated the speech act set of direct complaints performed by American and Russian native speakers. His findings showed that speakers in each language group made use of the same range of semantic categories in the speech act set of direct complaints, but the frequency and order of these categories differed. Speakers in both cultures structured their complaints differently, as they assigned different values to politeness. Speakers in American culture tried to minimize the degree of imposition upon interlocutors in a complaint situation, while Russians preferred straightforwardness over the utilization of face-saving strategies.

4. Conclusion The present study showed that, compared to native English and Chinese speakers, native Spanish speakers take longer to identify speech acts. Like native English speakers, native Spanish speakers show interference because of the activation of the speech act term; but in contrast to both native English and Chinese speakers, they do not show an increase in errors. In contrast to native English speakers, Spanish speakers did not show a significant priming effect for the probe word in relation to the speech act performed in the utterance. In conclusion, we found evidence for automatic speech act recognition in Spanish speakers in one of two tasks, as well as evidence suggesting that overall cognitive ability and mental state reasoning are relevant for speech act recognition. Knowing how culture affects speech act performance could help to reduce problems in intercultural communication. Understanding the specific ways in which a speech act is usually performed in a certain language and culture could help increase language competence in second language learners. Many empirical studies have established that second language speakers might fail to communicate effectively, even when they have excellent grammatical and lexical knowledge of the target language, because they fail to perform speech acts according to the rules. This issue can be settled if they are instructed

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in both grammatical and pragmatic rules of language (Blum-kulka, 1983; Blum-Kulka, 1982; Blum-Kulka and Olshtain, 1984; Olshtain and Blum-Kulka, 1985). Declarations of interest None. Acknowledgements CONACYT for financial support [scholarship #621367 to L-H, GL; project #225 to GM], to Azalea Reyes for technical support, Sarael Alcauter for critical review of the protocol, and Jessica Gonzalez-Norris for style correction and editing. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.pragma.2018.12.013. References
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noma de Me
xico. The focus of her research has been Giovanna L. Licea Haquet is a PhD student at the Instituto de Neurobiología, Universidad Nacional Auto the neural and cognitive basis of speech acts. To test this hypothesis, she uses behavioral and neuroimaging techniques.
squez-Upegui is professor of linguistics, and the coordinator of the doctoral program on Linguistics at the Facultad de Lenguas y Letras, UniEva P. Vela
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taro. The focus of her research has been prosody, pragmatics and speech analysis. versidad Auto Thomas Holtgraves is professor of psychological science at Ball State University in Muncie, Indiana, USA. He conducts interdisciplinary research, supported by the National Science Foundation and the National Institutes of Health, into multiple facets of language and social psychology. He is editor of the Oxford Handbook of Language and Social Psychology (Oxford University Press, 2014), as well as the author of “Social Psychology and Language: Words, Utterances and Conversations” in the Handbook of Social Psychology (Fiske, et al., 2010; Wiley) and Language as Social Action: Social Psychology and Language Use (Holtgraves, 2002).
noma de Me
xico. The focus of her research has been the study of Magda Giordano is a researcher at the Instituto de Neurobiología, Universidad Nacional Auto changes in behavior as a result of insult or injury to the central nervous system; the search for reparation strategies, such as neural transplants; and the evaluation of the effects of environmental toxicants. The basal ganglia are her model of study. She is currently interested in the possible participation of these nuclei in cognitive function in humans, in particular in the neural and cognitive basis of pragmatic language. To test this hypothesis, she uses behavioral and neuroimaging techniques.