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Robust speech recognition apparatus and method for Bayesian feature enhancement using independent vector analysis and reverberation parameter reestimation
Robust speech recognition apparatus and method for Bayesian feature enhancement using independent vector analysis and reverberation parameter reestimation
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机译：使用独立矢量分析和混响参数重新估计进行贝叶斯特征增强的鲁棒语音识别设备和方法
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摘要
The present invention relates to a voice recognition device, which enhances the Bayesian features by using re-estimated echo filter parameters and an independent vector analysis, and a method thereof. The voice recognition method includes the steps of: (a) converting and outputting the signals of each frequency band by executing a short-range Fourier transformation operation with multiple voice signals input from the outside; (b) estimating independent vector analysis (IVA) noise signals and IVA target sound signals by executing an IVA operation with the sound signals in the frequency bands; (c) extracting voice properties by using the hidden Markov model (HMM) based Bayesian feature enhancement (BFE) from the IVA target sound signals estimated by the IVA; (d) using the IVA target sound signals to scale the IVA noise signals estimated by the IVA to extract noise features from the scaled IVA noise signals; (e) estimating the initial sound signals by enhancing the sound features by executing an HMM-based BFE operation using the initial setting values of the voice feature and echo filter parameters; (f) re-tracking the echo filter parameters by using the estimated initial sound signals and the noise features; and (g) finally tracking the sound signals by enhancing the sound features by using the re-tracked echo filter parameters.
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