A study on signal extraction in noisy and reverberant environment

噪声混响环境下信号提取的研究

• 批准号: 10680374
• 负责人: AKAGI Masato
• 金额: $ 1.98万
• 依托单位: School of Information Science Japan Advanced Institute of Science and Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1998
• 资助国家: 日本
• 起止时间: 1998 至 2000
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-10680374/
• 关键词: noise; reverberation; auditory mechanism; nerve firing; interaural time difference (ITD); signal direction estimation; fundamental frequency; キャンセレーション; 雑音抑圧; 聴覚末梢系

This research discusses models of speech enhancement and segregation based on knowledge about human psychoacoustics and auditory physiology. The cancellation model is used for enhancing speech. Special attention is paid to reducing noise by using a spatial filtering technique, and increasing the robustness of fundamental frequency estimation by using a frequency filtering technique. Both techniques adopt concepts of the cancellation model. In addition, some constraints related to the heuristic regularities proposed by Bregman are used to overcome the problem associated with segregating two acoustic sources. Simulated results show that both spatial and frequency filtering are useful in enhancing speech. As a result, these filtering methods can be used effectively at the front-end of automatic speech recognition systems, and for speech feature extraction. The sound segregation model can precisely extract a desired signal from a noisy signal even in waveforms.Additionally, this research discusses models of sound source direction estimation based on physiological data of mammal audition. The model can explain the relationship between transmission of temporal and phase information by nerve firing and accuracy of interaural time differences.

这项研究讨论了基于人类心理声学和听觉生理学知识的语音增强和隔离模型。消除模型用于增强语音。特别注意通过使用空间滤波技术来减少噪声，并通过使用频率滤波技术来增加基频估计的鲁棒性。两种技术都采用消除模型的概念。此外，与布雷格曼提出的启发式规则相关的一些约束用于克服与分离两个声源相关的问题。模拟结果表明，空间和频率滤波对于增强语音都很有用。因此，这些过滤方法可以有效地用于自动语音识别系统的前端，并用于语音特征提取。即使在波形中，声音分离模型也可以从噪声信号中精确地提取出所需信号。此外，本研究还讨论了基于哺乳动物听觉生理数据的声源方向估计模型。该模型可以解释神经放电传递的时间和相位信息与耳间时间差的准确性之间的关系。

项目成果

Ito, K.and Akagi, M.: "A study on temporal information based on the synchronization index using a computational model"Proc.WESTPRAC7. 263-266 (2000)

Ito, K. 和 Akagi, M.：“使用计算模型对基于同步索引的时间信息进行研究”Proc.WESTPRAC7。

Unoki,M.and Akagi,M.: "A method of signal extraction from noisy signal based on auditory scene analysis"Speech Communication. 27,3-4. 261-279 (1999)

Unoki,M. 和 Akagi,M.：“基于听觉场景分析的噪声信号提取信号的方法”语音通信。

鵜木,赤木: "聴覚の情景解析に基づいた雑音下の調波復合音の一抽出法"電子情報通信学会論文誌. J82-A,10. 1497-1507 (1999)

Uoki，Akagi：“基于听觉场景分析的噪声下谐波解耦声音的提取方法”，电子、信息和通信工程师学会学报 J82-A，10. 1497-1507 (1999)。

Akagi,Mizumachi Ishimoto and Unokl: "Speech enhancement and segregation based on human auditory mechanims"Proc.IS2000,Aizu. 246-253 (2000)

Akagi、Mizumachi Ishimoto 和 Unokl：“基于人类听觉机制的语音增强和分离”Proc.IS2000，会津。

Unoki,M. and Akagi,M.: "Segregation of vowel in background noise using the method of segregating two acoustic sources based on auditory scene analysis"Proc.CASA99, IJCAI-99, Stockholm. 51-60 (1999)

宇野木，M.