Improving speech intelligibility in noise by SII-dependent preprocessing using frequency-dependent amplification and dynamic range compression
Improving speech intelligibility in noise by SII-dependent preprocessing using frequency-dependent amplification and dynamic range compression
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DOI：
10.21437/interspeech.2013-769
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
H. Schepker;J. Rennies;S. Doclo
中科院分区：
文献类型：
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作者：
H. Schepker;J. Rennies;S. Doclo
在这方面的贡献，提出了一种新的预处理算法，以提高在噪声中的语音清晰度，保持信号的功率处理前后。建议AdaptDRC算法由两个时间和频率依赖的阶段，这两个功能的估计SII。第一级应用依赖于时间和频率的放大，而第二级应用依赖于时间和频率的动态范围压缩（DRC）。与竞争扬声器（CS）和语音成形噪声（SSN）的实验表明，增加语音清晰度的四个不同的客观措施，与语音清晰度相关的广泛的SNR。在飓风挑战的框架内进行的听力测试与175名受试者证实了这些发现，并显示高达20.5%的SSN和12.3%的CS的可理解性的改善。
In this contribution, a new preprocessing algorithm to improve speech intelligibility in noise is proposed, which maintains the signal power before and after processing. The proposed AdaptDRC algorithm consists of two timeand frequency-dependent stages, which are both functions of the estimated SII. The first stage applies a timeand frequency-dependent amplification, while the second stage applies a timeand frequency-dependent dynamic range compression (DRC). Experiments with a competing speaker (CS) and a speech-shaped noise (SSN) show an increase in speech intelligibility for a wide range of SNRs for four different objective measures that are correlated with speech intelligibility. Listening tests conducted within the framework of the Hurricane Challenge with 175 subjects confirm these findings and show improvements of up to 20.5% in intelligibility for SSN and 12.3% for CS.