33 research outputs found
Lexical Diversity, Lexical Sophistication, and Predictability for Speech in Multiple Listening Conditions
When talkers anticipate that a listener may have difficulty understanding their speech, they adopt a speaking style typically described as “clear speech.” This speaking style includes a variety of acoustic modifications and has perceptual benefits for listeners. In the present study, we examine whether clear speaking styles also include modulation of lexical items selected and produced during naturalistic conversations. Our results demonstrate that talkers do, indeed, modulate their lexical selection, as measured by a variety of lexical diversity and lexical sophistication indices. Further, the results demonstrate that clear speech is not a monolithic construct. Talkers modulate their speech differently depending on the communication situation. We suggest that clear speech should be conceptualized as a set of speaking styles, in which talkers take the listener and communication situation into consideration
Multidimensional Signals and Analytic Flexibility: Estimating Degrees of Freedom in Human-Speech Analyses
Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions
Multidimensional Signals and Analytic Flexibility: Estimating Degrees of Freedom in Human-Speech Analyses
Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions
Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses
Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions
Listeners beware: Speech production may be bad for learning speech sounds
Available online 14 November 2015Spoken language requires individuals to both perceive and produce speech. Because both
processes access lexical and sublexical representations, it is commonly assumed that perception
and production involve cooperative processes. However, few studies have directly
examined the nature of the relationship between the two modalities, particularly how producing
speech influences speech perception. In a series of experiments, we examine the
counter-intuitive finding that learning perceptual representations can be disrupted by producing
tokens during training. We investigate whether this disruption can be alleviated by
prior experience with the speech sounds, and whether the cause of the disruption is production
of the particular sound being learned, or is a more general conflict between the
production system and the system that develops new perceptual representations. Our
results paint a more competitive relationship between perception and production than
might be assumed and suggest that both demands inherent to production and cognitive
demands modulate this relationship
Just give it time: Differential effects of disruption and delay on perceptual learning
Published online: 11 March 2022Speech perception and production are critical skills when acquiring a new language. However, the nature of the relationship
between these two processes is unclear, particularly for non-native speech sound contrasts. Although it has been assumed that
perception and production are supportive, recent evidence has demonstrated that, under some circumstances, production can
disrupt perceptual learning. Specifically, producing the to-be-learned contrast on each trial can disrupt perceptual learning of that
contrast. Here, we treat speech perception and speech production as separate tasks. From this perspective, perceptual learning
studies that include a production component on each trial create a task switch. We report two experiments that test how task
switching can disrupt perceptual learning. One experiment demonstrates that the disruption caused by switching to production is
sensitive to time delays: Increasing the delay between perception and production on a trial can reduce and even eliminate
disruption of perceptual learning. The second experiment shows that if a task other than producing the to-be-learned contrast
is imposed, the task-switching component of disruption is not influenced by a delay. These experiments provide a new understanding
of the relationship between speech perception and speech production, and clarify conditions under which the two
cooperate or compete.This work was supported by the National Science Foundation
Grants BCS-1734166, BCS-1941739, by Economic and Social Research
Council (UK) Grant #ES/R006288/1, Ministerio de Ciencia E Inovacion
(Spain) Grant # PSI2017-82563-P, by Ayuda Centro de Excelencia
Severo Ochoa (Spain) SEV-2015-0490, and by Grant PIBA18-29 from
the Basque Governmen
Listeners beware: Speech production may be bad for learning speech sounds
Available online 14 November 2015Spoken language requires individuals to both perceive and produce speech. Because both
processes access lexical and sublexical representations, it is commonly assumed that perception
and production involve cooperative processes. However, few studies have directly
examined the nature of the relationship between the two modalities, particularly how producing
speech influences speech perception. In a series of experiments, we examine the
counter-intuitive finding that learning perceptual representations can be disrupted by producing
tokens during training. We investigate whether this disruption can be alleviated by
prior experience with the speech sounds, and whether the cause of the disruption is production
of the particular sound being learned, or is a more general conflict between the
production system and the system that develops new perceptual representations. Our
results paint a more competitive relationship between perception and production than
might be assumed and suggest that both demands inherent to production and cognitive
demands modulate this relationship
Recommended from our members
The phonetics of vowel intrusion in Sgi Bara
We provide a phonetic examination of intrusive vowels in Sgi Bara [jil]. These vowels are inserted in predictable places, and their quality (either [i], [ɨ], or [u]) is also predictable, so they are not considered phonemic. We demonstrate that they differ from phonemic vowels in their duration, being shorter; and in their articulation, being more peripheral; but not in their intensity. We then demonstrate how this phonetic understanding of the difference between intrusive and phonemic vowels can be used to answer phonological questions about Sgi Bara. We offer two case studies: phonologically ambiguous sequences of high vowels, and frequent two-word combinations that may be univerbating. The results confirm the existence of a distinction between intrusive and phonemic vowels
Recommended from our members
Performance pay and non-native language comprehension: Can we learn to understand better when we’re paid to listen?
Non-native speech is difficult for native listeners to understand. While listeners can learn to understand non-native speech after exposure, it is unclear how to optimize this learning. Experimental subjects transcribed non-native speech and were paid either a flat rate or based on their performance. Participants who were paid based on performance demonstrated improved performance overall and faster learning than participants who were paid a flat rate. These results suggest that exposure alone is not sufficient to optimize learning of non-native speech and that current models of this process must be revised to account for the effects of motivation and incentive
How Good Does This Sound? Examining Listeners’ Second Language Proficiency and Their Perception of Category Goodness in Their Native Language
Language learners often transfer the sounds and prosody of their native language into their second language, but this influence can also flow in the opposite direction, with the second language influencing the first. Among other variables, language proficiency is known to affect the degree and directionality of cross-linguistic influence. However, little is known about how second language learning affects listeners’ perception of their native language. To begin addressing this gap, we examined the relationship between learners’ second language proficiency and their category goodness ratings in their native language. Thirty-nine English-speaking learners of Spanish listened to English words that began with voiced and voiceless stop consonants and were asked to rate how well the word represented the intended word on a 5-point scale. To create a voicing continuum, we manipulated the voice onset time of the word-initial stop in each target item from 125 ms of prevoicing to 100 ms of aspiration, in 25 ms steps. Proficiency did not affect the perception of voiced targets, but both proficiency and L2 stop production affected the perception of voiceless targets