46 citations · 66 across the 13 of their papers we have counts for
7 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…
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…
Room Geometry Estimation from Room Impulse Responses using Convolutional Neural Networks
Wangyang Yu, W. Bastiaan Kleijn
We describe a new method to estimate the geometry of a room given room impulse responses. The method utilises convolutional neural networks to estimate the room geometry and uses t…
Directional emphasis in ambisonics
W. Bastiaan Kleijn
We describe an ambisonics enhancement method that increases the signal strength in specified directions at low computational cost. The method can be used in a static setup to empha…