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响度轮廓会影响普通话声调识别:声码器模拟与人工耳蜗

Loudness Contour Can Influence Mandarin Tone Recognition: Vocoder Simulation and Cochlear Implants.

作者信息

Meng Qinglin, Zheng Nengheng, Li Xia

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2017 Jun;25(6):641-649. doi: 10.1109/TNSRE.2016.2593489. Epub 2016 Jul 20.

Abstract

Lexical tone recognition with current cochlear implants (CI) remains unsatisfactory due to significantly degraded pitch-related acoustic cues, which dominate the tone recognition by normal-hearing (NH) listeners. Several secondary cues (e.g., amplitude contour, duration, and spectral envelope) that influence tone recognition in NH listeners and CI users have been studied. This work proposes a loudness contour manipulation algorithm, namely Loudness-Tone (L-Tone), to investigate the effects of loudness contour on Mandarin tone recognition and the effectiveness of using loudness cue to enhance tone recognition for CI users. With L-Tone, the intensity of sound samples is multiplied by gain values determined by instantaneous fundamental frequencies (F0s) and pre-defined gain- F0 mapping functions. Perceptual experiments were conducted with a four-channel noise-band vocoder simulation in NH listeners and with CI users. The results suggested that 1) loudness contour is a useful secondary cue for Mandarin tone recognition, especially when pitch cues are significantly degraded; 2) L-Tone can be used to improve Mandarin tone recognition in both simulated and actual CI-hearing without significant negative effect on vowel and consonant recognition. L-Tone is a promising algorithm for incorporation into real-time CI processing and off-line CI rehabilitation training software.

摘要

由于与音高相关的声学线索显著退化,当前人工耳蜗(CI)的词汇声调识别仍然不尽人意,而这些线索在正常听力(NH)听众的声调识别中占主导地位。已经对一些影响NH听众和CI使用者声调识别的次要线索(例如,幅度轮廓、时长和频谱包络)进行了研究。这项工作提出了一种响度轮廓操纵算法,即响度-声调(L-声调),以研究响度轮廓对汉语声调识别的影响,以及使用响度线索增强CI使用者声调识别的有效性。使用L-声调时,声音样本的强度乘以由瞬时基频(F0)和预定义的增益-F0映射函数确定的增益值。在NH听众和CI使用者中使用四通道噪声带声码器模拟进行了感知实验。结果表明:1)响度轮廓是汉语声调识别的一个有用的次要线索,尤其是在音高线索显著退化时;2)L-声调可用于改善模拟和实际CI听力中的汉语声调识别,而对元音和辅音识别没有显著负面影响。L-声调是一种很有前景的算法,可纳入实时CI处理和离线CI康复训练软件中。

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