自适应抗噪的清/浊/静音判决算法

Adaptive anti-noise unvoiced / voiced / silence detection algorithm

清/浊/静音判决(UVS)是语音压缩、合成以及识别中的一个重要参数。为了解决传统判决方法训练过程复杂,导致语音编码效率低的问题,给出一种无训练过程的判决方法。提取基于循环平均幅度差的特征参量,利用判决参数间的相关性,自适应调整阈值,实现清/浊/静音判决。该判决方法具有很好的抗噪声干扰能力,有效提高判决的准确率。测试结果表明:该算法简化了清/浊/静音判决的计算量,清音误判率降低了10%,浊音误判率保持在4%以内;将该算法应用于低速率语音编码方案MELP(mixed excitation linear prediction)0.6 kbps的清浊音判决中,解码后的合成语音质量优于原始MELP编码方案,PESQ分数提高0.3,具有较好的可懂度和自然度。

The Unvoiced/ Voiced/ Silence detection UVS provides a preliminary acoustic segment which is a key parameter in speech compression synthesis and recognition.The complication of traditional UVS methods？？ training procedure causes low efficiency of speech vocoder.To solve this problem a UVS detection without training proceeding is proposed in this paper.After new characteristic parameters of unvoiced and voiced signal are extracted adaptable threshold is proposed based on the correlation of those parameters.With its perfect an？ti？noise ability the correct rate of this detection improves sharply.The simulation result shows that this algorithm not only simplifies the unvoiced/ voiced/ silence detection but also efficiently decreases 10% of unvoiced and maintains lower than 4% of voiced discrimination error.The improved 0.6 kbps MELP vocoder applying this detection algorithm gets a 0.3 higher PESQ score and better synthetic speech performance compared with original vocoder which produces good natural and intelligible speech.