1 code implementation • 13 Aug 2020 • Dipjyoti Paul, Muhammed PV Shifas, Yannis Pantazis, Yannis Stylianou
Intelligibility enhancement as quantified by the Intelligibility in Bits (SIIB-Gauss) measure shows that the proposed Lombard-SSDRC TTS system shows significant relative improvement between 110% and 130% in speech-shaped noise (SSN), and 47% to 140% in competing-speaker noise (CSN) against the state-of-the-art TTS approach.
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.
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.