高质量的0.6 kb/s声码器算法

为满足语音信息存贮和交流对极低速率下语音压缩编码的需求,提出了一种0.6 kb/s声码器算法.此算法基于线性预测正弦激励模型,在极低码率下获得高质量的合成语音,提出清浊音定位和量化方法,应用了多帧参数联合矢量量化技术,以及多带正弦混合激励、谱增强等技术.主观听觉测试显示,在0.6 kb/s的速率下,此声码器合成语音不仅具有高可懂度而且具有一定的自然度,诊断押韵测试(DRT)的分数为89.5%, 而且在10-2的随机误码的信道条件下仍然具有很好的可懂度.实验表明 利用帧间参数相关性及矢量量化的方法可以将编码速率大幅度压低而保持较高清晰度.

High quality 0.6 kb/s speech coding algorithm

A 0.6 kb/s high quality vocoder was developed to encode phonetic information at very low bit rates. The algorithm is based on a sinusoidally excited linear prediction model and uses multi frame joint vector quantification, multi band mixing excitation, sub band voicing strength parameter prediction, and adaptive spectral enhancement to obtain high quality synthetic speech with a low bit rate. Simulation results show that the synthesized speech is intelligible with reasonable naturalness. The diagnostic rhyme test score was 89.5% in the formal test. The vocoder is robust in a noisy environment and is still intelligible with a bit error rate of 10 -2 . The results suggest that the use of relative frame parameters and vector qualitification can greatly reduce the bit rate while maintaining clarity.