对比经典与神经语音编码器在噪声下的可懂度表现
Assessing the Impact of Noise and Speech Enhancement on the Intelligibility of Speech Codecs
- 测试不同编码器在干净与嘈杂环境中的语音可懂度
- 传统编码器在噪声下表现优于神经编码器，语音增强可显著提升效果
- 自动语音识别结果与主观评分高度相关，适合做客观评估
语音可懂度是通信中语音编码器的基本要求。近年来，极低码率的神经语音编码器受到关注，亟需评估其在真实场景下的可懂度是否得到保留。本文评估了经典与神经语音编码器在干净与噪声条件下的可懂度及听觉努力程度，并进一步考察了语音增强（SE）在编码前的应用效果，模拟实际音频处理流程。结果表明，经典编码器比神经编码器更具抗噪能力；语音增强可显著提升受噪声影响较大的编码器的可懂度和听觉舒适度。当可懂度达到饱和时，听觉努力能揭示更细微的差异。此外，基于自动语音识别的客观可懂度指标与按条件平均的主观可懂度评分高度相关。
原文摘要 · Abstract (English)
Preserving speech intelligibility is a minimum requirement for speech codecs in communication. Recently, very low-bitrate neural codecs have gained interest for replacing classical codecs, reinforcing the need to evaluate whether intelligibility is preserved in realistic scenarios. In this paper, we evaluate the intelligibility and listening effort of classical and neural speech codecs in clean and noisy conditions. Further, we assess the impact of speech enhancement (SE) before coding, simulating a possible audio processing pipeline. The results show that classical codecs are more noise robust than neural codecs. Further, SE can lead to significant intelligibility and listening effort improvements for codecs otherwise negatively affected by noise. Listening effort reveals nuanced differences when intelligibility is saturated. Lastly, objective intelligibility based on automatic speech recognition is highly correlated with subjective intelligibility scores averaged per condition.
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