基于线性预测系数自适应前后向量化的可变速率MELP语音编码

VARIABLE-RATE MELP SPEECH CODER BASED ON ADAPTIVE FORWARD-BACKWARD QUANTIZATION OF LINEAR PREDICTIVE COEFFICIENTS

该文基于LPC的自适应前后向量化技术,提出了一种可变速率的混合激励线性预测MELP语音编码算法。该算法中,采用当前语音帧(前向LPC)或前面某帧已合成语音帧(后向LPC)进行线性预测,当采用后向LPC时,只需传输时间序列编码,故减少了LPC系数的平均编码比特。计算机模拟表明,该算法与标准MELP算法合成的语音质量相当,但显著减少了LPC的传输带宽,从而明显降低了MELP平均编码速率。

In this paper, based on LPC adaptive forward-backward quantization, a novel variable-rate MELP speech coder is proposed, in which linear prediction is done by using either the current (forward LPC) or previously decoded (backward LPC) speech frames. The backward LPC scheme shall be applied, i.e., the LPC coefficients based on the previously decoded optimal speech frame are used to encode the current frame and only the time sequence code shall be transmitted to the decoder, so, average LPC bit number becomes smaller. Computer simulation shows significant average overall bit rate reduction is achieved without compromising the decoded speech quality.