Blind dereverberation of monaural speech signals based on harmonic structure

Nakatani, Tomohiro; Miyoshi, Masato; Kinoshita, Keisuke

doi:10.1002/scj.20509

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…One possible way in blind dereverberation is to use the speech characteristics. For example, the harmonic structure of speech can be used [15,16]. This method needs the fundamental frequency from reverberated speech to be accurately estimated, which is very difficult [17], and it does not seem to restore the consonant (nonharmonic) parts in speech.…”

Section: Rd International Universal Communication Symposiummentioning

confidence: 99%

Normalization on the modulation spectrum of the subband temporal envelopes for automatic speech recognition in reverberant environments

Unoki

Nakamura

2009

Proceedings of the 3rd International Universal Communication Symposium

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In this study, we proposed a feature extraction method based on the subband temporal envelopes (STEs) and their normalization for reverberated speech recognition. The STEs were extracted by using a series of constant bandwidth bandpass filters with Hilbert transform followed by a low-pass filtering. In the normalization, both the modulation spectrum (MS) of the subband temporal envelopes of the clean and reverberated speech are normalized to a reference MS calculated from a clean speech data set. Based on the normalized subband MS, the inverse Fourier transform was used to restore the subband temporal envelopes. We tested the proposed method on speech recognition in a reverberant room with different speaker to microphone distance (SMD). For comparison, the recognition performance of using the traditional Mel-cepstral coefficients with mean and variance normalization were used as the baseline. Experimental results showed that, by averaging the SMDs from 50 cm to 400 cm, there was a 44.96% relative improvement by only using subband temporal envelope processing, and further a 15.68% relative improvement by using the normalization on the subband modulation spectrum. Totally, there was about a 53.59% relative improvement, which was better than those of using other temporal filtering and normalization methods.

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Section: Rd International Universal Communication Symposiummentioning

confidence: 99%

Normalization on the modulation spectrum of the subband temporal envelopes for automatic speech recognition in reverberant environments

Unoki

Nakamura

2009

Proceedings of the 3rd International Universal Communication Symposium

View full text Add to dashboard Cite

show abstract

“…One possible way of utilizing blind dereverberation is to use speech characteristics. For example, the harmonic structure of speech can be used [13,14]. This method needs the fundamental frequency from reverberant speech to be accurately estimated, which is difficult [15], and it does not seem to restore the consonant (nonharmonic) parts in speech.…”

Section: Introductionmentioning

confidence: 99%

Comparative evaluation of modulation-transfer-function-based blind restoration of sub-band power envelopes of speech as a front-end processor for automatic speech recognition systems

Unoki

Akagi

2008

Acoust. Sci. & Tech.

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To reduce speech degradation in reverberant environments, we previously proposed a modulation-transfer-function (MTF)-based method of speech dereverberation. By considering the temporal modulation properties of speech, and the exponential decay properties of the power envelope of the impulse response of room acoustics, we obtained the following MTF relation: the sub-band power envelope of reverberant speech that can be represented as a convolution between the sub-band power envelope of clean speech and the power envelope of the impulse response of room acoustics. On the basis of the MTF relation, inverse MTF filtering can be applied to restoring the power envelopes of reverberant speech. Therefore, the impulse response of the room acoustics in this restoration dose not need to be measured at any time since we model the power envelope of the impulse response as an exponential decay function. We have tested how effective this method is as a front-end for automatic speech recognition (ASR) systems in artificial and real reverberant environments. Reverberant speech signals were created by simply convoluting clean speech (AURORA-2J database) with the artificially produced or real impulse responses of room acoustics. A method based on the auditory power spectrum was used as a baseline for comparison. Compared with the baseline, the proposed method for artificial reverberant environments produced a 35.67% relative improvement in the error reduction rate (on average, for reverberation times from 0.2 to 2.0 s), and for real reverberant environments (43 reverberant impulse responses), it produced a 25.78% relative improvement in the error reduction rate. The results demonstrate that our new approach can improve the robustness of speech-recognition systems in reverberant environments, and it performs better than conventional methods.

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Blind dereverberation of monaural speech signals based on harmonic structure

Cited by 2 publications

References 14 publications

Normalization on the modulation spectrum of the subband temporal envelopes for automatic speech recognition in reverberant environments

Normalization on the modulation spectrum of the subband temporal envelopes for automatic speech recognition in reverberant environments

Comparative evaluation of modulation-transfer-function-based blind restoration of sub-band power envelopes of speech as a front-end processor for automatic speech recognition systems

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