LP-MVDR谱比方法在耳语检测中的意义

Arpit Mathur, R. Hegde
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引用次数: 4

摘要

本文提出了一种新的谱比检测方法,用于在正常语音流中检测语音片段。该方法基于计算线性预测(LP)谱与最小方差失真响应(MVDR)谱的比值。发现线性预测方法和LP残差法本身都不足以对语音信号中的中高频进行建模。相反,MVDR方法对所有频率的谱都具有鲁棒性。在提出的频谱比方法中,利用两者之间的频谱估计差异将具有较少谐波和较多噪声的耳语段从正常发音的语音段中分离出来。将该方法与LP残差法和光谱平坦度法进行了对比分析。在CHAINS数据库上进行耳语检测实验。从ROC曲线和耳语化错误率可以看出,该方法有了合理的改进。
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Significance of the LP-MVDR spectral ratio method in Whisper Detection
A new spectral ratio method is proposed in this paper for detecting whispered segments within a normally phonated speech stream. The method is based on computing the ratio of the linear Prediction(LP) spectrum to the minimum variance distortion less response (MVDR) spectrum. Both the linear prediction method and the LP residual method by themselves are found to be inadequate in modelling medium to high frequencies in the speech signal. On the contrary, the MVDR method shows robustness in modelling spectra of all frequencies. This difference in spectral estimation between the two is utilized in the proposed spectral ratio method to separate whispered segments having less harmonics and more noise from normally phonated segments of speech. A comparative analysis of the proposed method with other methods like the LP residual and the spectral flatness methods is described. Whisper Detection experiments are conducted on the CHAINS database. The proposed method indicates reasonable improvements as noted from the ROC curves and the whisper diarization error rate.
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