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A mixed excitation LPC vocoder model for low bit rate speech coding

机译:低比特率语音编码的混合激励LPC声码器模型

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Traditional pitch-excited linear predictive coding (LPC) vocoders use a fully parametric model to efficiently encode the important information in human speech. These vocoders can produce intelligible speech at low data rates (800-2400 b/s), but they often sound synthetic and generate annoying artifacts such as buzzes, thumps, and tonal noises. These problems increase dramatically if acoustic background noise is present at the speech input. This paper presents a new mixed excitation LPC vocoder model that preserves the low bit rate of a fully parametric model but adds more free parameters to the excitation signal so that the synthesizer can mimic more characteristics of natural human speech. The new model also eliminates the traditional requirement for a binary voicing decision so that the vocoder performs well even in the presence of acoustic background noise. A 2400-b/s LPC vocoder based on this model has been developed and implemented in simulations and in a real-time system. Formal subjective testing of this coder confirms that it produces natural sounding speech even in a difficult noise environment. In fact, diagnostic acceptability measure (DAM) test scores show that the performance of the 2400-b/s mixed excitation LPC vocoder is close to that of the government standard 4800-b/s CELP coder.
机译:传统的音调激励线性预测编码(LPC)声码器使用完全参数化模型来有效编码人类语音中的重要信息。这些声码器可以以低数据速率(800-2400 b / s)产生可理解的语音,但是它们通常听起来是合成的,并且会产生令人讨厌的伪像,例如嗡嗡声,重击声和音调噪声。如果语音输入中出现声学背景噪声,这些问题将急剧增加。本文提出了一种新的混合激励LPC声码器模型,该模型保留了全参数模型的低比特率,但为激励信号添加了更多自由参数,因此合成器可以模仿自然人语音的更多特征。新模型还消除了对二进制发声决策的传统要求,因此,即使在存在声学背景噪声的情况下,声码器也能表现良好。已经开发了基于该模型的2400-b / s LPC声码器,并已在仿真和实时系统中实现。对该编码器进行的正式主观测试证实,即使在困难的噪声环境下,它也可以发出自然的语音。实际上,诊断可接受性度量(DAM)测试分数表明2400-b / s混合激励LPC声码器的性能接近政府标准4800-b / s CELP编码器的性能。

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