改進的后濾波波束形成器語音增強算法
The Modified Post-Filter Beamforming for Speech Enhancement
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摘要: 該文提出了一種具有后濾波的波束形成器的語音增強改進算法。該算法主要解決維納濾波器的理想信號功率譜估計,結合自功率譜減法和互功率譜減法計算出盡可能多的功率譜估計值,以使平均結果更接近于真實值,同時修正了聲源移動引起的互功率譜變化。實驗結果信噪比提高5dB以上,汽車環(huán)境中基于隱含馬爾可夫模型(HMM)的小詞匯量短語識別達到84%。從信噪比、平均譜距離和語音識別率可以看出該算法有效去除了原始算法中易殘留的低頻噪聲,減少了語音信號失真。
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關鍵詞:
- 語音增強; 傳聲器陣列; 波束形成器
Abstract: A modified Wiener post-filter beamforming for speech enhancement is presented. The proposed algorithm focuses on the estimation of the ideal signals power spectrum for the Wiener filter, both auto-correlation and cross-correlation are taken into consideration to obtain as more power spectrum estimations as possible, the average of which produces more accurate result. Meanwhile, the alteration of cross-correlation caused by the moving speaker is revised. The performance of the algorithm has been evaluated from Signal to Noise Ratio (SNR), Average Log Spectrum Distance (ALSD) and speech recognition rate. The SNR is improved by 5 dB. The command recognition rate based on Hidden Markov Model (HMM) in the car environment reaches 84%. The low frequency noise that still remains after the process of the primary method is reduced by the proposed method, and the speech signal distortion is also decreased. -
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