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Statistical models for speech dereverberation
2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2009This paper discusses a statistical-model-based approach to speech dereverberation. With this approach, we first define parametric statistical models of probability density functions (pdfs) for a clean speech signal and a room transmission channel, then estimate the model parameters, and finally recover the clean speech signal by using the pdfs with the
Takuya Yoshioka +3 more
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Cepstrum based deconvolution for speech dereverberation
Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002We propose an algorithm for the restoration of speech that has been degraded through addition of multiple echoes. The proposed scheme processes the outputs of two microphones using cepstra operations and the theory of signal reconstruction from phase only.
A.P. Petropulu, S. Subramaniam
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Guided spectrogram filtering for speech dereverberation
Applied Acoustics, 2018Guided filtering is a computationally efficient and powerful technique used in image processing applications, such as edge-preserving smoothing, details enhancing and single image dehazing. In this paper, we propose a novel single channel speech dereverberation method using guided spectrogram filtering by considering a speech spectrogram as an image ...
Zheng, Chengshi +3 more
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Group sparsity for mimo speech dereverberation
2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2015Reverberation can severely affect the speech signals recorded in a room, possibly leading to a significantly reduced speech quality and intelligibility. In this paper we present a batch algorithm employing a signal model based on multi-channel linear prediction in the short-time Fourier transform domain. Aiming to achieve multiple-input multiple-output
Ante Jukic +3 more
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Amplitude Consistent Enhancement for Speech Dereverberation
Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence, 2020The mapping and masking methods based on deep learning are both essential methods for speech dereverberation at present, which typically enhance the amplitude of the reverberant speech while letting the reverberant phase unprocessed. The reverberant phase and enhanced amplitude are used to synthesize the target speech.
Chunlei Liu, Longbiao Wang, Jianwu Dang
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Cepstrum-based deconvolution for speech dereverberation
IEEE Transactions on Speech and Audio Processing, 1996We present a blind deconvolution-based approach for the restoration of speech degraded by the acoustic environment. The proposed scheme processes the outputs of two microphones using cepstra operations and the theory of signal reconstruction from phase only.
S. Subramaniam, A.P. Petropulu, C. Wendt
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Calculating Inverse Filters for Speech Dereverberation
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2008Speech dereverberation is one of the most difficult tasks in acoustic signal processing. Of the various problems involved in this task, this paper highlights “over-whitening,” which flattens the characteristics of recovered speech. This distortion sometimes happens when inverse filters are directly calculated from microphone signals. This paper reviews
M. MIYOSHI, M. DELCROIX, K. KINOSHITA
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Phase-Aware Speech Enhancement and Dereverberation
2023of speech quality (PESQ) measure.
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Learning spectral mapping for speech dereverberation
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014Reverberation distorts human speech and usually has negative effects on speech intelligibility, especially for hearing-impaired listeners. It also causes performance degradation in automatic speech recognition and speaker identification systems. Therefore, the dereverberation problem must be dealt with in daily listening environments. We propose to use
Kun Han, Yuxuan Wang, DeLiang Wang
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Blind dereverberation of a speech signal
Acoustical Physics, 2008Possibilities to eliminate the reverberation from a speech signal are investigated by applying the method based on the determination of the parameters of the reverberation frequency response from the cepstrum of the reverberation-distorted signal.
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