Literature DB >> 19390234

On the possible role of brain rhythms in speech perception: intelligibility of time-compressed speech with periodic and aperiodic insertions of silence.

Oded Ghitza1, Steven Greenberg.   

Abstract

This study was motivated by the prospective role played by brain rhythms in speech perception. The intelligibility - in terms of word error rate - of natural-sounding, synthetically generated sentences was measured using a paradigm that alters speech-energy rhythm over a range of frequencies. The material comprised 96 semantically unpredictable sentences, each approximately 2 s long (6-8 words per sentence), generated by a high-quality text-to-speech (TTS) synthesis engine. The TTS waveform was time-compressed by a factor of 3, creating a signal with a syllable rhythm three times faster than the original, and whose intelligibility is poor (<50% words correct). A waveform with an artificial rhythm was produced by automatically segmenting the time-compressed waveform into consecutive 40-ms fragments, each followed by a silent interval. The parameters varied were the length of the silent interval (0-160 ms) and whether the lengths of silence were equal ('periodic') or not ('aperiodic'). The performance curve (word error rate as a function of mean duration of silence) was U-shaped. The lowest word error rate (i.e., highest intelligibility) occurred when the silence was 80 ms long and inserted periodically. This is also the condition for which word error rate increased when the silence was inserted aperiodically. These data are consistent with a model (TEMPO) in which low-frequency brain rhythms affect the ability to decode the speech signal. In TEMPO, optimum intelligibility is achieved when the syllable rhythm is within the range of the high theta-frequency brain rhythms (6-12 Hz), comparable to the rate at which segments and syllables are articulated in conversational speech. (c) 2009 S. Karger AG, Basel.

Entities:  

Mesh:

Year:  2009        PMID: 19390234     DOI: 10.1159/000208934

Source DB:  PubMed          Journal:  Phonetica        ISSN: 0031-8388            Impact factor:   1.759


  95 in total

1.  Neurophysiological origin of human brain asymmetry for speech and language.

Authors:  Benjamin Morillon; Katia Lehongre; Richard S J Frackowiak; Antoine Ducorps; Andreas Kleinschmidt; David Poeppel; Anne-Lise Giraud
Journal:  Proc Natl Acad Sci U S A       Date:  2010-10-18       Impact factor: 11.205

2.  Membrane potential dynamics of populations of cortical neurons during auditory streaming.

Authors:  Brandon J Farley; Arnaud J Noreña
Journal:  J Neurophysiol       Date:  2015-08-12       Impact factor: 2.714

3.  Theta and Gamma Bands Encode Acoustic Dynamics over Wide-Ranging Timescales.

Authors:  Xiangbin Teng; David Poeppel
Journal:  Cereb Cortex       Date:  2020-04-14       Impact factor: 5.357

Review 4.  Temporal context in speech processing and attentional stream selection: a behavioral and neural perspective.

Authors:  Elana M Zion Golumbic; David Poeppel; Charles E Schroeder
Journal:  Brain Lang       Date:  2012-01-29       Impact factor: 2.381

5.  A Multivariate Analytic Approach to the Differential Diagnosis of Apraxia of Speech.

Authors:  Alexandra Basilakos; Grigori Yourganov; Dirk-Bart den Ouden; Daniel Fogerty; Chris Rorden; Lynda Feenaughty; Julius Fridriksson
Journal:  J Speech Lang Hear Res       Date:  2017-12-20       Impact factor: 2.297

Review 6.  Facial expressions and the evolution of the speech rhythm.

Authors:  Asif A Ghazanfar; Daniel Y Takahashi
Journal:  J Cogn Neurosci       Date:  2014-01-23       Impact factor: 3.225

7.  Rhythmic auditory cortex activity at multiple timescales shapes stimulus-response gain and background firing.

Authors:  Christoph Kayser; Caroline Wilson; Houman Safaai; Shuzo Sakata; Stefano Panzeri
Journal:  J Neurosci       Date:  2015-05-20       Impact factor: 6.167

8.  Detection and identification of speech sounds using cortical activity patterns.

Authors:  T M Centanni; A M Sloan; A C Reed; C T Engineer; R L Rennaker; M P Kilgard
Journal:  Neuroscience       Date:  2013-11-26       Impact factor: 3.590

9.  Decoding time for the identification of musical key.

Authors:  Morwaread M Farbood; Jess Rowland; Gary Marcus; Oded Ghitza; David Poeppel
Journal:  Atten Percept Psychophys       Date:  2015-01       Impact factor: 2.199

10.  An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions.

Authors:  Sanne Ten Oever; Andrea E Martin
Journal:  Elife       Date:  2021-08-02       Impact factor: 8.140

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.