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

机译:在普通话音调的解析和未解决的组件中的语音脑干表达的声音脑干表示

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摘要

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 (FFRENV) or fine structure (FFRTFS), respectively. The neural representation of the F0 strength reflected by the FFRENV 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 FFRENV 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 FFRTFS 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 FFRTFS to resolved harmonics was significantly larger than to unresolved harmonics. Spearman's correlation showed that the FFRENV F0 strength to unresolved harmonics was correlated with tone identification performance in noise (0 dB SNR). These results showed that the FFRENV 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.
机译:准确对语音间距的看法在语音理解中起着至关重要的作用,特别是对于普通话等音调语言。词汇色调主要通过声波形的基本频率(F0)轮廓来区分。已经表明,听觉系统可以从解决的和未解决的谐波中提取F0,解决的谐波的音调识别性能优于未解决的谐波。为了评估安静和语音噪声中普通话音调的解析和未解决的组件的神经响应,我们记录了频率跟踪响应。在这项研究中,使用了四种类型的刺激:在安静和言语噪声中,具有仅解决的谐波或仅解析的谐波或唯一的谐波的语音。将频率跟踪响应(FFR)记录到交替极性刺激,并分别加入或减去以增强对包膜(FFRENV)或细结构(FFRTF)的神经响应。由FFRONV反射的F0强度的神经表示通过在光谱域中的F0处的时间域和峰值相位锁定值(PLV)中的峰值自相关值评估。两个评估方法表明,安静的FFRENV F0强度明显强于包括未解决的谐波的噪音,但不是包括解决谐波的言论。由FFRTFS反射的时间细结构的神经表示由PLV在近近F1(F0的第4位)的谐波中进行评估。 FFRTFS近邻FFRTFS的谐波(F0)的谐波的PLV显着大于未解决的谐波。 Spearman的相关性表明,FFRENV F0强度与未解决的谐波的强度与噪声识别性能(0 dB SNR)相关。这些结果表明,具有解决谐波的语音声音的FFRENV F0强度不受噪音的影响。相比之下,与未解决的谐波对语音声音的响应,与安静相比,噪音明显较小。我们的结果表明,编码已解决的谐波比编码信封更重要,用于噪声中的音调识别性能。

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