Single microphone speech enhancement systems have typically shown limited performance, while multiple microphone systems based on a least-squares error criterion have shown encouraging results in some contexts. In this paper we formulate a new approach to multiple microphone speech enhancement. Specifically, we formulate a maximum likelihood (ML) problem for estimating the parameters needed for...

In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhanceme...

Spectral mask estimation using bidirectional long short-term memory (BLSTM) neural networks has been widely used in various speech enhancement applications, and it has achieved great success when it is applied to multichannel enhancement techniques with a mask-based beamformer. However, when these masks are used for single channel speech enhancement they severely distort the speech signal and m...

Numerous studies have investigated the effectiveness of audio-visual multimodal learning for speech enhancement (AVSE) tasks, seeking a solution that uses visual data as auxiliary and complementary input to reduce noise noisy signals. Recently, we proposed lite (LAVSE) algorithm car-driving scenario. Compared conventional AVSE systems, LAVSE requires less online computation some extent solves u...