상태변수 기반의 실시간 음성검출 알고리즘의 최적화
Optimization of State-Based Real-Time Speech Endpoint Detection Algorithm
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초록
In this paper, a speech endpoint detection algorithm is proposed. The proposed algorithm is a kind of state transition-based ones for speech detection. To reject short-duration acoustic pulses which can be considered noises, it utilizes duration information of all detected pulses. For the optimization of parameters related with pulse lengths and energy threshold to detect speech intervals, an exhaustive search scheme is adopted while speech recognition rates are used as its performance index. Experimental results show that the proposed algorithm outperforms the baseline state-based endpoint detection algorithm. At 5 dB input SNR for the beamforming input, the word recognition accuracies of its outputs were 78.5% for human voice noises and 81.1% for music noises.
Abstract
In this paper, a speech endpoint detection algorithm is proposed. The proposed algorithm is a kind of state transition-based ones for speech detection. To reject short-duration acoustic pulses which can be considered noises, it utilizes duration information of all detected pulses. For the optimization of parameters related with pulse lengths and energy threshold to detect speech intervals, an exhaustive search scheme is adopted while speech recognition rates are used as its performance index. Experimental results show that the proposed algorithm outperforms the baseline state-based endpoint detection algorithm. At 5 dB input SNR for the beamforming input, the word recognition accuracies of its outputs were 78.5% for human voice noises and 81.1% for music noises.
참고문헌 (10)
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- Shen, J., "Robust Entropy-based Endpoint Detection for Speech Recognition in Noisy Environments", Int. Conf. on Spoken Lang. Processing (1998)
- Zhang, X., "Speech Endpoint Detection Method Based on Wavelet Coefficient Variance and Sub-Band Amplitude Variance", First International Conference on Innovative Computing, Information and Control, 통권 : 3, pp.83~86 (2006)
- Rabiner, L., "Digital Processing of Speech Signals" (1978), Prentice Hall
- Li, Q., "Robust endpoint detection and energy normalization for real-time speech and speaker recognition", IEEE Trans. Speech and Audio Processing, 10(3), pp.146~157 (2002)
- Han, S., "Robust GSC -based speech enhancement for human machine interface", IEEE Trans. Consumer Electronics, 56(2), pp.965~970 (2010)
- "ETSI ES 202 212(2005). speech processing, transmission, and quality aspects(STQ), v.1.1.2", ~ (2005)
- Wu, B., "Robust endpoint detection algorithm based on the adaptive band-partitioning spectral entropy in adverse environments", IEEE Trans. Speech and Audio Processing, 13(5), pp.762~775 (2005)