半盲方法分离真实世界的混合语音

Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290) Pub Date : 2002-08-07 DOI:10.1109/IJCNN.2002.1007681

F. Tordini, F. Piazza

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引用次数: 10

摘要

研究了在多通道盲反卷积算法中引入先验信息的可能性。最大似然(ML)方法允许人们将声音的一个重要特征，即音高，自然地引入“盲”模型，消除非线性，并通过计算机辅助声音分析(CASA)和贝叶斯理论等相关研究领域显示出生产性污染的优势。

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A semi-blind approach to the separation of real world speech mixtures

The possibility of introducing a-priori information into multichannel blind deconvolution algorithms is investigated. The maximum likelihood (ML) approach allows one to introduce an important feature of the voice, namely the pitch, naturally into the 'blind' model, removing the nonlinearity and showing the advantages of productive contaminations by such related research fields as computer-aided sound analysis (CASA) and Bayesian theory.

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Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290)

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