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Auditory Brainstem Representation of the Voice Pitch Contours in the Resolved and Unresolved Components of Mandarin Tones

Accurate perception of voice pitch plays a vital role in speech understanding, especially for tonal languages such as Mandarin. Lexical tones are primarily distinguished by the fundamental frequency (F0) contour of the acoustic waveform. It has been shown that the auditory system could extract the F...

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Detalles Bibliográficos
Autores principales: Peng, Fei, McKay, Colette M., Mao, Darren, Hou, Wensheng, Innes-Brown, Hamish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250765/
https://www.ncbi.nlm.nih.gov/pubmed/30505262
http://dx.doi.org/10.3389/fnins.2018.00820
Descripción
Sumario:Accurate perception of voice pitch plays a vital role in speech understanding, especially for tonal languages such as Mandarin. Lexical tones are primarily distinguished by the fundamental frequency (F0) contour of the acoustic waveform. It has been shown that the auditory system could extract the F0 from the resolved and unresolved harmonics, and the tone identification performance of resolved harmonics was better than unresolved harmonics. To evaluate the neural response to the resolved and unresolved components of Mandarin tones in quiet and in speech-shaped noise, we recorded the frequency-following response. In this study, four types of stimuli were used: speech with either only-resolved harmonics or only-unresolved harmonics, both in quiet and in speech-shaped noise. Frequency-following responses (FFRs) were recorded to alternating-polarity stimuli and were added or subtracted to enhance the neural response to the envelope (FFR(ENV)) or fine structure (FFR(TFS)), respectively. The neural representation of the F0 strength reflected by the FFR(ENV) was evaluated by the peak autocorrelation value in the temporal domain and the peak phase-locking value (PLV) at F0 in the spectral domain. Both evaluation methods showed that the FFR(ENV) F0 strength in quiet was significantly stronger than in noise for speech including unresolved harmonics, but not for speech including resolved harmonics. The neural representation of the temporal fine structure reflected by the FFR(TFS) was assessed by the PLV at the harmonic near to F1 (4th of F0). The PLV at harmonic near to F1 (4th of F0) of FFR(TFS) to resolved harmonics was significantly larger than to unresolved harmonics. Spearman's correlation showed that the FFR(ENV) F0 strength to unresolved harmonics was correlated with tone identification performance in noise (0 dB SNR). These results showed that the FFR(ENV) F0 strength to speech sounds with resolved harmonics was not affected by noise. In contrast, the response to speech sounds with unresolved harmonics, which were significantly smaller in noise compared to quiet. Our results suggest that coding resolved harmonics was more important than coding envelope for tone identification performance in noise.