李如玮, 鲍长春. 一种基于分带谱熵和谱能量的语音端点检测算法[J]. 北京工业大学学报, 2007, 33(9): 920-924.
    引用本文: 李如玮, 鲍长春. 一种基于分带谱熵和谱能量的语音端点检测算法[J]. 北京工业大学学报, 2007, 33(9): 920-924.
    LI Ru-wei, BAO Chang-chun. A Speech Endpoint Detection Algorithm Based on the Band-partitioning Spectral Entropy and Spectral Energy[J]. Journal of Beijing University of Technology, 2007, 33(9): 920-924.
    Citation: LI Ru-wei, BAO Chang-chun. A Speech Endpoint Detection Algorithm Based on the Band-partitioning Spectral Entropy and Spectral Energy[J]. Journal of Beijing University of Technology, 2007, 33(9): 920-924.

    一种基于分带谱熵和谱能量的语音端点检测算法

    A Speech Endpoint Detection Algorithm Based on the Band-partitioning Spectral Entropy and Spectral Energy

    • 摘要: 语音端点检测的精确度直接影响语音识别的准确度.在噪声环境下,语音端点检测很困难.信噪比下降,语音端点检测的正确率也随之下降,同时,噪声类型的变化影响端点检测的正确率.为此,提出了一种改进的、适合在电话语音城市名识别系统中应用的端点检测算法,并结合分带谱熵和谱能量形成了一个新的特征参数集,利用该参数集进行端点检测,弥补了分别采用分带谱熵和谱能量进行端点检测的缺陷,提高了检测性能.

       

      Abstract: The accuracy of speech recognition directly depends on accurate endpoint detection.Endpoint detec- tion is a very difficult task in the noise environment.It will be degraded with the decrease of SNR and differ- ent noise affects the accuracy of speech recognition.As a result,this paper proposed an endpoint detection ap- proach which is applicable to the telephone speech recognition system for city's name.The approach inte- grates band-partitioning spectral entropy and spectral energy to form a set of new feature parameters that can compensating the drawback of entropy and energy so that the performance of the detection is improved.

       

    /

    返回文章
    返回