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Significance of Emotionally Significant Regions of Speech for Emotive to Neutral Conversion

机译:情绪重要地区对中立转换情绪的重要意义

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Most of the speech processing applications suffer from a degradation in performance when operated in emotional environments. The degradation in performance is mostly due to a mismatch between developing and operating environments. Model adaptation and feature adaptation schemes have been employed to adapt speech systems developed in neutral environments to emotional environments. In this study, we have considered only anger emotion in emotional environments. In this work, we have studied the signal level conversion from anger emotion to neutral emotion. Emotion in human speech is concentrated over a small region in the entire utterance. The regions of speech that are highly influenced by the emotive state of the speaker is are considered as emotionally significant regions of an utterance. Physiological constraints of human speech production mechanism are explored to detect the emotionally significant regions of an utterance. Variation of various prosody parameters (Pitch, duration and energy) based on their position in the sentences is analyzed to obtain the modification factors. Speech signal in the emotionally significant regions is modified using the corresponding modification factor to generate the neutral version of the anger speech. Speech samples from Indian Institute of Technology Kharagpur Simulated Emotion Speech Corpus (IITKGP-SESC) are used in this study. A subjective listening test is performed for evaluating the effectiveness of the proposed conversion.
机译:大多数语音处理应用程序在在情绪环境中运行时遭受性能的降级。性能下降主要是由于开发和操作环境之间的不匹配。模型适配和特征适应方案已经采用来调整中性环境中开发的语音系统到情绪环境。在这项研究中,我们只考虑了情绪环境中的愤怒情绪。在这项工作中,我们研究了从愤怒情绪到中性情绪的信号水平转化。人类演讲中的情感集中在整个话语中的一个小区域。受到扬声器的情绪状态受到高度影响的言语区域被认为是一种情感重要的话语。探讨了人类语音生产机制的生理限制,以检测话语的情绪重要地区。分析了基于句子中的位置的各种韵律参数(间距,持续时间和能量)的变化,以获得修改因子。使用相应的修改因子来修改情绪有效区域中的语音信号,以产生愤怒语音的中性版本。来自印度理工学院Kharagpur的语音样本kharagpur模拟情感语音语料库(Iitkgp-sec)在本研究中使用。执行主观听力测试,用于评估所提出的转换的有效性。

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