有效量化无退化的语音编码语音参数

M. Morise, Genta Miyashita
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引用次数: 0

摘要

在带声码器的统计参数语音合成(SPSS)系统中,需要降低语音参数的维数,许多SPSS系统都采用了压缩语音参数。本文介绍了基频、谱包络和非周期三个语音参数的量化算法。在全频带语音(采样频率在40khz以上的语音)中,根据前人的研究,频谱包络和非周期的维数可以分别降为50维和5维。将无退化的量化编码与不编码的语音参数合成的语音进行了比较。高效量化对于使用图形处理单元(GPU)计算的研究是有效的,因为最近的GPU支持16位浮点计算。我们做了两个主观评估。第一次评估确定了每个语音参数中适当的量化位。我们得到了fo中的9位值,频谱包络中的13位值,非周期中的3位值。第二次评估验证了我们提出的编码的有效性。由于数据块通常使用8的倍数,因此我们在评估中使用16个量化位来表示0,16个用于频谱包络,8个用于非周期性。结果表明,我们提出的算法在不编码的情况下获得了与语音参数几乎相同的音质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient quantization of vocoded speech parameters without degradation
In a statistical parametric speech synthesis (SPSS) system with a vocoder, the dimensions of speech parameters need to be reduced, and many SPSS systems have used companded speech parameters. This paper introduces quantization algorithms for 3 speech parameters: fundamental frequency (fo), spectral envelope, and aperiodicity. In full-band speech (speech with a sampling frequency above 40 kHz), the dimensions of the spectral envelope and the aperiodicity can be reduced to 50 and 5 dimensions based on previous studies. This paper compares the quantization coding without degradation with speech synthesized by the speech parameters without coding. Efficient quantization would be effective for a study that uses graphics processing unit (GPU) computing because recent GPUs support 16-bit floating-point computing. We did two subjective evaluations. The first evaluation determined the appropriate quantization bits in each speech parameter. We obtained the 9 bit values in fo, 13 bit values in the spectral envelope, and 3 bit values in the aperiodicity. The second evaluation verified the effectiveness of our proposed coding. Since a multiple of eight is generally used for data chunks, we employed the 16 quantization bits for fo, 16 for the spectral envelope, and 8 for aperiodicity in the evaluation. The results showed that our proposed algorithm achieved almost all the same sound quality as the speech parameters without coding.
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