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Tomoko Kawase

3 accepted papers

2017

Supervised source enhancement composed of nonnegative auto-encoders and complementarity subtraction

ICASSP 2017accepted

A method for constructing deep neural networks (DNNs) for accurate supervised source enhancement is proposed. Attempts were made in previous studies to estimate the power spectral densities (PSDs) of sound sources, which are used to estimate Wiener filters for source enhancement, from the output of…

Cited by 0SourceScholar
2016

Pinpoint extraction of distant sound source based on DNN mapping from multiple beamforming outputs to prior SNR

ICASSP 2016accepted

We propose a method for estimating the prior signal-to-noise ratio (SNR), which is used for calculating the Wiener filter for distant sound source extraction, from output signals of beamforming using statistical mapping based on the deep neural network (DNN). Since informative features to estimate t…

Cited by 17SourceScholar
2016

Real-time integration of statistical model-based speech enhancement with unsupervised noise PSD estimation using microphone array

ICASSP 2016accepted

We propose a technique of multi-channel speech enhancement based on integration of beamforming and statistical model-based speech enhancement to clearly extract the target speech, even in very noisy environments. Conventional microphone array-based techniques estimate speech and noise power spectral…

Cited by 3SourceScholar