扩展的高频率可以提高语音识别:来自于空间语音混合中的自动语音识别的证据
Zhe-Chen Guo1, Bharath Chandrasekaran1
1Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois 60208, USA.
The Journal of the Acoustical Society of America
|October 23, 2025
概括
扩展高频 (EHF) 直接改善在杂的环境中语音识别,特别是对辅音. 这一好处有助于语音感知,并支持它们在听力测试和语音识别系统中的使用.
科学领域:
- 听觉神经科学 听觉神经科学
- 语音处理 语音处理
- 机器学习 机器学习
背景情况:
- 8kHz以上的扩展高频 (EHF) 增强了噪音中的语音感知,但它们的确切作用仍在争论中.
- 目前尚不清楚EHF是否提供直接的语音线索,或间接反映耳健康.
研究的目的:
- 调查电波频段在具有挑战性的听觉条件下对语音识别的直接贡献.
- 通过使用声学自动语音识别 (ASR) 模型来克服人类在EHF值中的变化.
主要方法:
- 一个声学ASR模型 (CNN-BiLSTM) 被训练在VCTK体的语音上,在各种空间分离和目标对面具比率 (TMR) 上重新合成空间音频和面具干扰.
- 该模型从宽带和低通过 (8kHz截止) 语音的耳图解码了音符,以评估EHF的影响.
主要成果:
- 在所有空间分隔的掩盖条件下,EHF显著改善了音声识别,特别是在-9dB及以下的TMR.
- 在安静的听力条件下,没有观察到来自EHF的显著改善.
- 删除EHF不成比例地增加了辅音的语音错误率,与它们更高的光谱度保持一致.
结论:
- 超高频提供直接的声学线索,增强语音识别,特别是在语音掩饰场景中.
- 这些发现支持将EHF集成到临床声学评估中,并开发先进的ASR系统.
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