A non-causal FFTNet architecture for speech enhancement

1 code implementation • 8 Jun 2020 • Muhammed PV Shifas, Nagaraj Adiga, Vassilis Tsiaras, Yannis Stylianou

By suggesting a shallow network and applying non-causality within certain limits, the suggested FFTNet for speech enhancement (SE-FFTNet) uses much fewer parameters compared to other neural network based approaches for speech enhancement like WaveNet and SEGAN.

Speech Enhancement

A fully recurrent feature extraction for single channel speech enhancement

1 code implementation • arXiv 2020 • Muhammed PV Shifas, Santelli Claudio, Vassilis Tsiaras, Yannis Stylianou

Convolutional neural network (CNN) modules are widely being used to build high-end speech enhancement neural models.

Speech Enhancement

Speech intelligibility enhancement based on a non-causal Wavenet-like model

1 code implementation • Interspeech 2018 • Muhammed Shifas PV, Vassilis Tsiaras, Yannis Stylianou

Low speech intelligibility in noisy listening conditions makes more difficult our communication with others.

Speaker-independent raw waveform model for glottal excitation

no code implementations • 25 Apr 2018 • Lauri Juvela, Vassilis Tsiaras, Bajibabu Bollepalli, Manu Airaksinen, Junichi Yamagishi, Paavo Alku

Recent speech technology research has seen a growing interest in using WaveNets as statistical vocoders, i. e., generating speech waveforms from acoustic features.

Speech Synthesis Text-To-Speech Synthesis +1