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Antoni Rodríguez-fornells - One of the best experts on this subject based on the ideXlab platform.
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Neurophysiological evidence for the interplay of Speech Segmentation and word-referent mapping during novel word learning.
Neuropsychologia, 2016Co-Authors: Clément François, Matti Laine, Toni Cunillera, Enara Garcia, Antoni Rodríguez-fornellsAbstract:Learning a new language requires the identification of word units from continuous Speech (the Speech Segmentation problem) and mapping them onto conceptual representation (the word to world mapping problem). Recent behavioral studies have revealed that the statistical properties found within and across modalities can serve as cues for both processes. However, Segmentation and mapping have been largely studied separately, and thus it remains unclear whether both processes can be accomplished at the same time and if they share common neurophysiological features. To address this question, we recorded EEG of 20 adult participants during both an audio alone Speech Segmentation task and an audiovisual word-to-picture association task. The participants were tested for both the implicit detection of online mismatches (structural auditory and visual semantic violations) as well as for the explicit recognition of words and word-to-picture associations. The ERP results from the learning phase revealed a delayed learning-related fronto-central negativity (FN400) in the audiovisual condition compared to the audio alone condition. Interestingly, while online structural auditory violations elicited clear MMN/N200 components in the audio alone condition, visual-semantic violations induced meaning-related N400 modulations in the audiovisual condition. The present results support the idea that Speech Segmentation and meaning mapping can take place in parallel and act in synergy to enhance novel word learning.
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Time course and functional neuroanatomy of Speech Segmentation in adults.
NeuroImage, 2009Co-Authors: Toni Cunillera, Estela Camara, Juan M. Toro, Josep Marco-pallarés, Núria Sebastián-gallés, Hector Ortiz, Jesús Pujol, Antoni Rodríguez-fornellsAbstract:The present investigation was devoted to unraveling the time-course and brain regions involved in Speech Segmentation, which is one of the first processes necessary for learning a new language in adults and infants. A specific brain electrical pattern resembling the N400 language component was identified as an indicator of Speech Segmentation of candidate words. This N400 trace was clearly elicited after a short exposure to the words of the new language and showed a decrease in amplitude with longer exposure. Two brain regions were observed to be active during this process: the posterior superior temporal gyrus and the superior part of the ventral premotor cortex. We interpret these findings as evidence for the existence of an auditory-motor interface that is responsible for isolating possible candidate words when learning a new language in adults.
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Speech Segmentation is facilitated by visual cues.
Quarterly journal of experimental psychology (2006), 2009Co-Authors: Toni Cunillera, Matti Laine, Estela Camara, Antoni Rodríguez-fornellsAbstract:Evidence from infant studies indicates that language learning can be facilitated by multimodal cues. We extended this observation to adult language learning by studying the effects of simultaneous visual cues (nonassociated object images) on Speech Segmentation performance. Our results indicate that Segmentation of new words from a continuous Speech stream is facilitated by simultaneous visual input that it is presented at or near syllables that exhibit the low transitional probability indicative of word boundaries. This indicates that temporal audio-visual contiguity helps in directing attention to word boundaries at the earliest stages of language learning. Off-boundary or arrhythmic picture sequences did not affect Segmentation performance, suggesting that the language learning system can effectively disregard noninformative visual information. Detection of temporal contiguity between multimodal stimuli may be useful in both infants and second-language learners not only for facilitating Speech Segmentation, but also for detecting word-object relationships in natural environments.
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The effects of stress and statistical cues on continuous Speech Segmentation: an event-related brain potential study.
Brain research, 2006Co-Authors: Toni Cunillera, Juan M. Toro, Núria Sebastián-gallés, Antoni Rodríguez-fornellsAbstract:The study of the processes involved in Speech Segmentation has gained special relevance in recent years by trying to establish what type of information listeners use to segment the Speech signal into words. An event-related brain potential experiment was conducted in order to understand how two of these cues (statistical and stress cues) interact. The experiment consisted of the presentation of artificial Speech streams in which words were marked either by statistical cues alone, or by a combination of statistical and stress cues. As a baseline, comparison streams were also created with the same syllables but organized in random order. Results showed an N400 component that marks the on-line Segmentation of Speech into words, and an increased positivity (P2 component) for languages that include both types of cues. Possible implications of these results for the process of Speech Segmentation are discussed.
Marina Nespor - One of the best experts on this subject based on the ideXlab platform.
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Statistical Speech Segmentation in Tone Languages: The Role of Lexical Tones:
Language and speech, 2017Co-Authors: David M. Gómez, Jacques Mehler, Peggy Mok, Mikhail Ordin, Marina NesporAbstract:Research has demonstrated distinct roles for consonants and vowels in Speech processing. For example, consonants have been shown to support lexical processes, such as the Segmentation of Speech based on transitional probabilities (TPs), more effectively than vowels. Theory and data so far, however, have considered only non-tone languages, that is to say, languages that lack contrastive lexical tones. In the present work, we provide a first investigation of the role of consonants and vowels in statistical Speech Segmentation by native speakers of Cantonese, as well as assessing how tones modulate the processing of vowels. Results show that Cantonese speakers are unable to use statistical cues carried by consonants for Segmentation, but they can use cues carried by vowels. This difference becomes more evident when considering tone-bearing vowels. Additional data from speakers of Russian and Mandarin suggest that the ability of Cantonese speakers to segment streams with statistical cues carried by tone-bearing vowels extends to other tone languages, but is much reduced in speakers of non-tone languages.
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Co‐occurrence statistics as a language‐dependent cue for Speech Segmentation
Developmental science, 2016Co-Authors: Amanda Saksida, Alan Langus, Marina NesporAbstract:To what extent can language acquisition be explained in terms of different associative learning mechanisms? It has been hypothesized that distributional regularities in spoken languages are strong enough to elicit statistical learning about dependencies among Speech units. Distributional regularities could be a useful cue for word learning even without rich language-specific knowledge. However, it is not clear how strong and reliable the distributional cues are that humans might use to segment Speech. We investigate cross-linguistic viability of different statistical learning strategies by analyzing child-directed Speech corpora from nine languages and by modeling possible statistics-based Speech Segmentations. We show that languages vary as to which statistical Segmentation strategies are most successful. The variability of the results can be partially explained by systematic differences between languages, such as rhythmical differences. The results confirm previous findings that different statistical learning strategies are successful in different languages and suggest that infants may have to primarily rely on non-statistical cues when they begin their process of Speech Segmentation.
Sven L. Mattys - One of the best experts on this subject based on the ideXlab platform.
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Statistical learning for Speech Segmentation: Age-related changes and underlying mechanisms.
Psychology and aging, 2018Co-Authors: Shekeila D. Palmer, James Hutson, Sven L. MattysAbstract:Statistical learning (SL) is a powerful learning mechanism that supports word Segmentation and language acquisition in infants and young adults. However, little is known about how this ability changes over the life span and interacts with age-related cognitive decline. The aims of this study were to: (a) examine the effect of aging on Speech Segmentation by SL, and (b) explore core mechanisms underlying SL. Across four testing sessions, young, middle-aged, and older adults were exposed to continuous Speech streams at two different Speech rates, both with and without cognitive load. Learning was assessed using a two-alterative forced-choice task in which words from the stream were pitted against either part-words, which occurred across word boundaries in the stream, or nonwords, which never appeared in the stream. Participants also completed a battery of cognitive tests assessing working memory and executive functions. The results showed that Speech Segmentation by SL was remarkably resilient to aging, although age effects were visible in the more challenging conditions, namely, when words had to be discriminated from part-words, which required the formation of detailed phonological representations, and when SL was performed under cognitive load. Moreover, an analysis of the cognitive test data indicated that performance against part-words was predicted mostly by memory updating, whereas performance against nonwords was predicted mostly by working memory storage capacity. Taken together, the data show that SL relies on a combination of implicit and explicit skills, and that age effects on SL are likely to be linked to an age-related selective decline in memory updating. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Effects of syntactic expectations on Speech Segmentation.
Journal of experimental psychology. Human perception and performance, 2007Co-Authors: Sven L. Mattys, James F. Melhorn, Laurence WhiteAbstract:Although the effect of acoustic cues on Speech Segmentation has been extensively investigated, the role of higher order information (e.g., syntax) has received less attention. Here, the authors examined whether syntactic expectations based on subject-verb agreement have an effect on Segmentation and whether they do so despite conflicting acoustic cues. Although participants detected target words faster in phrases containing adequate acoustic cues ("spins" in take spins and "pins" in takes pins), this acoustic effect was suppressed when the phrases were appended to a plural context (those women take spins/*takes pins [with the asterisk indicating a syntactically unacceptable parse]). The syntactically congruent target ("spins") was detected faster regardless of the acoustics. However, a singular context (that woman *take spins/takes pins) had no effect on Segmentation, and the results resembled those of the neutral phrases. Subsequent experiments showed that the discrepancy was due to the relative time course of syntactic expectations and acoustics cues. Taken together, the data suggest that syntactic knowledge can facilitate Segmentation but that its effect is substantially attenuated if conflicting acoustic cues are encountered before full realization of the syntactic constraint.
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Integration of multiple Speech Segmentation cues: a hierarchical framework
Journal of experimental psychology. General, 2005Co-Authors: Sven L. Mattys, Laurence White, James F. MelhornAbstract:A central question in psycholinguistic research is how listeners isolate words from connected Speech despite the paucity of clear word-boundary cues in the signal. A large body of empirical evidence indicates that word Segmentation is promoted by both lexical (knowledge-derived) and sublexical (signal-derived) cues. However, an account of how these cues operate in combination or in conflict is lacking. The present study fills this gap by assessing Speech Segmentation when cues are systematically pitted against each other. The results demonstrate that listeners do not assign the same power to all Segmentation cues; rather, cues are hierarchically integrated, with descending weights allocated to lexical, segmental, and prosodic cues. Lower level cues drive Segmentation when the interpretive conditions are altered by a lack of contextual and lexical information or by white noise. Taken together, the results call for an integrated, hierarchical, and signal-contingent approach to Speech Segmentation.
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Stress versus coarticulation: toward an integrated approach to explicit Speech Segmentation.
Journal of experimental psychology. Human perception and performance, 2004Co-Authors: Sven L. MattysAbstract:Although word stress has been hailed as a powerful Speech-Segmentation cue, the results of 5 cross-modal fragment priming experiments revealed limitations to stress-based Segmentation. Specifically, the stress pattern of auditory primes failed to have any effect on the lexical decision latencies to related visual targets. A determining factor was whether the onset of the prime was coarticulated with the preceding Speech fragment. Uncoarticulated (i.e., concatenated) primes facilitated priming. Coarticulated ones did not. However, when the primes were presented in a background of noise, the pattern of results reversed, and a strong stress effect emerged: Stress-initial primes caused more priming than non-initial-stress primes, regardless of the coarticulatory cues. The results underscore the role of coarticulation in the Segmentation of clear Speech and that of stress in impoverished listening conditions. More generally, they call for an integrated and signal-contingent approach to Speech Segmentation.
Toni Cunillera - One of the best experts on this subject based on the ideXlab platform.
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Neurophysiological evidence for the interplay of Speech Segmentation and word-referent mapping during novel word learning.
Neuropsychologia, 2016Co-Authors: Clément François, Matti Laine, Toni Cunillera, Enara Garcia, Antoni Rodríguez-fornellsAbstract:Learning a new language requires the identification of word units from continuous Speech (the Speech Segmentation problem) and mapping them onto conceptual representation (the word to world mapping problem). Recent behavioral studies have revealed that the statistical properties found within and across modalities can serve as cues for both processes. However, Segmentation and mapping have been largely studied separately, and thus it remains unclear whether both processes can be accomplished at the same time and if they share common neurophysiological features. To address this question, we recorded EEG of 20 adult participants during both an audio alone Speech Segmentation task and an audiovisual word-to-picture association task. The participants were tested for both the implicit detection of online mismatches (structural auditory and visual semantic violations) as well as for the explicit recognition of words and word-to-picture associations. The ERP results from the learning phase revealed a delayed learning-related fronto-central negativity (FN400) in the audiovisual condition compared to the audio alone condition. Interestingly, while online structural auditory violations elicited clear MMN/N200 components in the audio alone condition, visual-semantic violations induced meaning-related N400 modulations in the audiovisual condition. The present results support the idea that Speech Segmentation and meaning mapping can take place in parallel and act in synergy to enhance novel word learning.
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Time course and functional neuroanatomy of Speech Segmentation in adults.
NeuroImage, 2009Co-Authors: Toni Cunillera, Estela Camara, Juan M. Toro, Josep Marco-pallarés, Núria Sebastián-gallés, Hector Ortiz, Jesús Pujol, Antoni Rodríguez-fornellsAbstract:The present investigation was devoted to unraveling the time-course and brain regions involved in Speech Segmentation, which is one of the first processes necessary for learning a new language in adults and infants. A specific brain electrical pattern resembling the N400 language component was identified as an indicator of Speech Segmentation of candidate words. This N400 trace was clearly elicited after a short exposure to the words of the new language and showed a decrease in amplitude with longer exposure. Two brain regions were observed to be active during this process: the posterior superior temporal gyrus and the superior part of the ventral premotor cortex. We interpret these findings as evidence for the existence of an auditory-motor interface that is responsible for isolating possible candidate words when learning a new language in adults.
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Speech Segmentation is facilitated by visual cues.
Quarterly journal of experimental psychology (2006), 2009Co-Authors: Toni Cunillera, Matti Laine, Estela Camara, Antoni Rodríguez-fornellsAbstract:Evidence from infant studies indicates that language learning can be facilitated by multimodal cues. We extended this observation to adult language learning by studying the effects of simultaneous visual cues (nonassociated object images) on Speech Segmentation performance. Our results indicate that Segmentation of new words from a continuous Speech stream is facilitated by simultaneous visual input that it is presented at or near syllables that exhibit the low transitional probability indicative of word boundaries. This indicates that temporal audio-visual contiguity helps in directing attention to word boundaries at the earliest stages of language learning. Off-boundary or arrhythmic picture sequences did not affect Segmentation performance, suggesting that the language learning system can effectively disregard noninformative visual information. Detection of temporal contiguity between multimodal stimuli may be useful in both infants and second-language learners not only for facilitating Speech Segmentation, but also for detecting word-object relationships in natural environments.
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The effects of stress and statistical cues on continuous Speech Segmentation: an event-related brain potential study.
Brain research, 2006Co-Authors: Toni Cunillera, Juan M. Toro, Núria Sebastián-gallés, Antoni Rodríguez-fornellsAbstract:The study of the processes involved in Speech Segmentation has gained special relevance in recent years by trying to establish what type of information listeners use to segment the Speech signal into words. An event-related brain potential experiment was conducted in order to understand how two of these cues (statistical and stress cues) interact. The experiment consisted of the presentation of artificial Speech streams in which words were marked either by statistical cues alone, or by a combination of statistical and stress cues. As a baseline, comparison streams were also created with the same syllables but organized in random order. Results showed an N400 component that marks the on-line Segmentation of Speech into words, and an increased positivity (P2 component) for languages that include both types of cues. Possible implications of these results for the process of Speech Segmentation are discussed.
Mariusz Ziolko - One of the best experts on this subject based on the ideXlab platform.
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Wavelet Transform in Speech Segmentation
Progress in Industrial Mathematics at ECMI 2008, 2010Co-Authors: Mariusz Ziolko, Jakub Galka, Tomasz DrwięgaAbstract:A non-uniform Speech Segmentation method based on discrete wavelet transform is used for the localization of phoneme boundaries. A vector of real values representing the digital Speech signal is decomposed into phone-like units by placing segment borders according to the result of the multiresolution analysis. The final decision on localization of boundaries is taken by analysis of the energy flow among the decomposition levels. Distribution-like event functions indicate events, regarded as the segment boundaries.
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INTERSpeech - Perceptual Wavelet Decomposition for Speech Segmentation
2010Co-Authors: Mariusz Ziolko, Bartosz Ziolko, Jakub Galka, Tomasz DrwięgaAbstract:A non-uniform Speech Segmentation method based on wavelet packet transform is used for the localisation of phoneme boundaries. Eleven subbands are chosen by applying the mean best basis algorithm. Perceptual scale is used for decomposition of Speech via Meyer wavelet in the wavelet packet structure. A real valued vector representing the digital Speech signal is decomposed into phone-like units by placing segment borders according to the result of the multiresolution analysis. The final decision on localisation of the boundaries is made by analysis of the energy flows among the decomposition levels. Index Terms: Speech Segmentation, wavelet packet transform, Speech recognition
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wavelet method of Speech Segmentation
European Signal Processing Conference, 2006Co-Authors: Bartosz Ziolko, Suresh Manandhar, Richard Wilson, Mariusz ZiolkoAbstract:In this paper a new method of Speech Segmentation is suggested. It is based on power fluctuations of the wavelet spectrum for a Speech signal. In most approaches to Speech recognition, the Speech signals are segmented using constant-time Segmentation. Constant Segmentation needs to use windows to decrease the boundary distortions. A more natural approach is to segment the Speech signals on the basis of time-frequency analysis. Boundaries are assigned in places where some energy of a frequency band rapidly changes. Most methods of non-constant Segmentation need training for particular data or are realized as a part of modelling. In this paper we apply the discrete wavelet transform (DWT) to analyse Speech signals, the resulting power spectrum and its derivatives. This information allows us to locate the boundaries of phonemes. It is the first stage of Speech recognition process. Additionally we present an evaluation by comparing our method with hand Segmentation. The Segmentation method proves effective for finding most phoneme boundaries. Results are more useful for Speech recognition than constant Segmentation.