An adaptive band-partitioning spectral entropy based speech detection in realistic noisy environments

Bing-Fei Wu, Kun Ching Wang

研究成果: Paper同行評審

3 引文 斯高帕斯(Scopus)

摘要

Generally, the feature parameters used for speech detection are highly sensitive to the environment. The performance of speech detection is severely degraded under realistic noisy environments since the characteristics of a speech signal cannot be fully expressed by those feature parameters. As a result, this study seeks the acoustic fingerprints of speech spectrogram as a robust feature to distinguish a speech from a non-speech, especially in adverse environments, and the fact that the frequency energies of difference types of noise are concentrated on different frequency bands [12], an ABSE (Adaptive Band-partitioning Spectral Entropy)-based speech detection algorithm is proposed to detect speech signals in adverse environments. Additionally, the ABSE-based algorithm is demonstrated to work in real-time with minimal processing delay. Experimental results indicate that the ABSE parameter is very effective for several SNRs (Signal to Noise Ratios) and various noise conditions. Furthermore, the proposed ABSE-based algorithm outperforms other approaches and is reliable in a real car.

原文English
頁面957-960
頁數4
出版狀態Published - 10月 2004
事件8th International Conference on Spoken Language Processing, ICSLP 2004 - Jeju, Jeju Island, Korea, Republic of
持續時間: 4 10月 20048 10月 2004

Conference

Conference8th International Conference on Spoken Language Processing, ICSLP 2004
國家/地區Korea, Republic of
城市Jeju, Jeju Island
期間4/10/048/10/04

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