非均匀韵律修饰在情绪条件下语音识别中的重要性

Vishnu Vidyadhara Raju Vegesna, Hari Krishna Vydana, S. Gangashetty, A. Vuppala
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引用次数: 8

摘要

训练和操作环境的不匹配会导致语音识别系统(ASR)的性能下降。造成这种不匹配的一个主要原因是在操作环境中存在表达性(情绪化)的语音。言语中的情绪主要造成音高、持续时间和能量等韵律参数的变化。这项工作的目的是提高语音识别系统的性能,在存在的情绪语音。本工作的重点是在不干扰现有ASR系统的情况下提高语音识别性能。通过调整中性数据集和情绪数据集之间相对差异的修正因子值,实现音调、持续时间和能量的韵律修正。使用统一和非统一韵律修饰方法生成情感语音的中性版本,用于语音识别。在研究过程中,使用IITKGP-SESC语料库构建ASR系统。对情绪(愤怒、快乐和同情)的语音识别系统进行了评估。用韵律修饰的情绪话语代替原有的情绪话语进行语音识别,可以明显改善ASR的表现。由于使用非均匀韵律修改方法,我们观察到准确率平均提高了5%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Importance of non-uniform prosody modification for speech recognition in emotion conditions
A mismatch in training and operating environments causes a performance degradation in speech recognition systems (ASR). One major reason for this mismatch is due to the presence of expressive (emotive) speech in operational environments. Emotions in speech majorly inflict the changes in the prosody parameters of pitch, duration and energy. This work is aimed at improving the performance of speech recognition systems in the presence of emotive speech. This work focuses on improving the speech recognition performance without disturbing the existing ASR system. The prosody modification of pitch, duration and energy is achieved by tuning the modification factors values for the relative differences between the neutral and emotional data sets. The neutral version of emotive speech is generated using uniform and non-uniform prosody modification methods for speech recognition. During the study, IITKGP-SESC corpus is used for building the ASR system. The speech recognition system for the emotions (anger, happy and compassion) is evaluated. An improvement in the performance of ASR is observed when the prosody modified emotive utterance is used for speech recognition in place of original emotive utterance. An average improvement around 5% in accuracy is observed due to the use of non-uniform prosody modification methods.
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