Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10370215 | Speech Communication | 2005 | 13 Pages |
Abstract
Most listeners have difficulty understanding speech in reverberant conditions. The purpose of this study is to investigate whether it is possible to reduce the degree of degradation of speech intelligibility in reverberation through the development of an algorithm. The modulation spectrum is the spectral representation of the temporal envelope of the speech signal. That of clean speech is dominated by components between 1 and 16 Hz centered at 4 Hz which is the most important range for human perception of speech. In reverberant conditions, the modulation spectrum of speech is shifted toward the lower end of the modulation frequency range. In this study, we proposed to enhance the important modulation spectral components prior to distortion of speech by reverberation. Word intelligibility in a carrier sentence was tested with the newly developed algorithm including two different filter designs in three reverberant conditions. The reverberant speech was simulated by convoluting clean speech with impulse responses measured in the actual halls. The experimental results show that modulation filtering incorporated into a pre-processing algorithm improves intelligibility for normal hearing listeners when (1) the modulation filters are optimal for a specific reverberant condition (i.e., T60Â =Â 1.1 s), and (2) consonants are preceded by highly powered segments. Under shorter (0.7 s) and longer (1.6 s) reverberation times, the modulation filtering in the current experiments, an Empirically-Designed (E-D) filter and a Data-Derived (D-D) filter, caused a slight performance decrement respectively. The results of this study suggest that further gains in intelligibility may be accomplished by re-design of the modulation filters suitable for other reverberant conditions.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Akiko Kusumoto, Takayuki Arai, Keisuke Kinoshita, Nao Hodoshima, Nancy Vaughan,