120 citations · 125 across the 4 of their papers we have counts for
6 papers · 1 filter
Handling Background Noise in Neural Speech Generation
Tom Denton, Alejandro Luebs, Felicia S. C. Lim +4
Recent advances in neural-network based generative modeling of speech has shown great potential for speech coding. However, the performance of such models drops when the input is n…
Generative Speech Coding with Predictive Variance Regularization
W. Bastiaan Kleijn, Andrew Storus, Michael Chinen +5
The recent emergence of machine-learning based generative models for speech suggests a significant reduction in bit rate for speech codecs is possible. However, the performance of…
ViSQOL v3: An Open Source Production Ready Objective Speech and Audio Metric
Michael Chinen, Felicia S. C. Lim, Jan Skoglund +3
Estimation of perceptual quality in audio and speech is possible using a variety of methods. The combined v3 release of ViSQOL and ViSQOLAudio (for speech and audio, respectively,)…
Generative Speech Enhancement Based on Cloned Networks
Michael Chinen, W. Bastiaan Kleijn, Felicia S. C. Lim +1
We propose to implement speech enhancement by the regeneration of clean speech from a salient representation extracted from the noisy signal. The network that extracts salient feat…
Salient Speech Representations Based on Cloned Networks
W. Bastiaan Kleijn, Felicia S. C. Lim, Michael Chinen +1
We define salient features as features that are shared by signals that are defined as being equivalent by a system designer. The definition allows the designer to contribute qualit…
Wavenet based low rate speech coding
W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs +4
Traditional parametric coding of speech facilitates low rate but provides poor reconstruction quality because of the inadequacy of the model used. We describe how a WaveNet generat…