Abstractness of human speech sound representations

Hestvik, Arild; Shinohara, Yasuaki; Durvasula, Karthik; Verdonschot, Rinus G.; Sakai, Hiromu

doi:10.1016/j.brainres.2020.146664

Cited by 10 publications

(7 citation statements)

References 72 publications

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“…The finding of an order effect highlights the importance of examining a range of factors that might influence the study outcome. Specifically, we observed that the amplitude of the MMN was smaller to deviant stimulus if it appeared as the standard in the first block, similar to the finding of Hestvik and Durvasula (2016) and Hestvik et al (2020). This pattern suggests a lingering memory trace of the deviant when previously presented as the standard.…”

Section: Other Factorssupporting

confidence: 81%

“…This latter finding cannot easily be explained in terms of the acoustic properties of the stimuli. Hestvik et al (2020) argue that their findings support an underspecification account, but it will also be important to consider the finding in relation to a prototypicality effect.…”

Section: Support For Underspecificationmentioning

confidence: 93%

“…But this pattern is consistent with an acoustic explanation (Maiste et al, 1995), as well as the underspecification account. However, lending increased support to a phonological account was the finding that Japanese listeners revealed an MMN amplitude asymmetry in the opposite direction of English speakers, using the same stimuli as Hestvik and Durvasula (2016) (Hestvik et al, 2020). This latter finding cannot easily be explained in terms of the acoustic properties of the stimuli.…”

Section: Support For Underspecificationmentioning

confidence: 99%

“…It is well-established that early language-specific experience has shaped adult speech perception and neural processing (Näätänen et al, 2007;Shafer et al, accepted). For an underspecification model to show viability, it needs to explain cross-linguistic differences as well as universal patterns (e.g., Hestvik et al, 2020). It is not clear that it can do this better than a prototype model.…”

Section: Category Goodnessmentioning

confidence: 99%

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Neural Representation of the English Vowel Feature [High]: Evidence From /ε/ vs. /ɪ/

Shafer

2021

Front. Hum. Neurosci.

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Many studies have observed modulation of the amplitude of the neural index mismatch negativity (MMN) related to which member of a phoneme contrast [phoneme A, phoneme B] serves as the frequent (standard) and which serves as the infrequent (deviant) stimulus (i.e., AAAB vs. BBBA) in an oddball paradigm. Explanations for this amplitude modulation range from acoustic to linguistic factors. We tested whether exchanging the role of the mid vowel /ε/ vs. high vowel /ɪ/ of English modulated MMN amplitude and whether the pattern of modulation was compatible with an underspecification account, in which the underspecified height values are [−high] and [−low]. MMN was larger for /ε/ as the deviant, but only when compared across conditions to itself as the standard. For the within-condition comparison, MMN was larger to /ɪ/ deviant minus /ε/ standard than to the reverse. A condition order effect was also observed. MMN amplitude was smaller to the deviant stimulus if it had previously served as the standard. In addition, the amplitudes of late discriminative negativity (LDN) showed similar asymmetry. LDN was larger for deviant /ε/ than deviant /ɪ/ when compared to themselves as the standard. These findings were compatible with an underspecification account, but also with other accounts, such as the Natural Referent Vowel model and a prototype model; we also suggest that non-linguistic factors need to be carefully considered as additional sources of speech processing asymmetries.

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Section: Other Factorssupporting

confidence: 81%

Section: Support For Underspecificationmentioning

confidence: 93%

Section: Support For Underspecificationmentioning

confidence: 99%

Section: Category Goodnessmentioning

confidence: 99%

See 2 more Smart Citations

Neural Representation of the English Vowel Feature [High]: Evidence From /ε/ vs. /ɪ/

Shafer

2021

Front. Hum. Neurosci.

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“…There is now emerging evidence favouring not only underspecified features being stored, as described above, but also cross-linguistic evidence that auditory cortex supports featural underspecification in distinct laryngeal systems. Using Japanese, where [voiced] is the putatively marked feature, Hestvik et al, (2020) observed a larger MMN when voiced stops were the standard compared to when voiceless stops were the standard. And using Danish, Højlund et al, (2019) observed a larger MMN when [d] was the standard compared to when [tʰ] was the standard.…”

Section: Discussionmentioning

confidence: 98%

Unified Coding of Spectral and Temporal Phonetic Cues: Electrophysiological Evidence for Abstract Phonological Features

Monahan¹,

Schertz²,

Fu³

et al. 2021

Preprint

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Understanding how the brain represents speech sounds is necessary to delineate the mapping between the acoustic signal and words stored in long-term memory. Spoken word recognition models and phonological theory propose that abstract features are linguistic units that play a central role in speech processing. The current goal was to determine whether the brain represents abstract phonological features. English phonology functionally codes stops and fricatives as voiced or voiceless. Fricatives and stops, however, encode voicing in distinct phonetic manners. Fricatives use a spectral cue, while stops use a temporal cue. Participants listened to syllables in a many-to-one oddball design while their EEG was recorded. A critical design element was the presence of inter-category variation within the standards. In one block, both voiceless stops and fricatives were the standard. In the other block, both voiced stops and fricatives were the standards. A many-to-one relationship exists only if the standards are grouped together. Oscillatory activity was also measured. Results show an MMN effect in the voiceless standards block–an asymmetric MMN–and increased beta-band oscillatory power prior to voiceless standards stimulus-onset. These findings suggest that (i) the brain constructed an auditory memory trace of the standards based on the shared [voiceless] feature, which is only functionally defined, (ii) voiced consonants are underspecified and, (iii) features can serve as a basis for predictive processing. Taken together, these results point toward the brain’s ability to functionally code distinct phonetic cues together and that abstract features can be used to parse the continuous acoustic signal.

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Neurocomputational Properties of Speech Sound Perception and Production

Grimaldi

2023

Neuromethods

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Abstractness of human speech sound representations

Cited by 10 publications

References 72 publications

Neural Representation of the English Vowel Feature [High]: Evidence From /ε/ vs. /ɪ/

Neural Representation of the English Vowel Feature [High]: Evidence From /ε/ vs. /ɪ/

Unified Coding of Spectral and Temporal Phonetic Cues: Electrophysiological Evidence for Abstract Phonological Features

Neurocomputational Properties of Speech Sound Perception and Production

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