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9 papers · 1 filter
Speech dereverberation constrained on room impulse response characteristics
Louis Bahrman, Mathieu Fontaine, Jonathan Le Roux +1
Single-channel speech dereverberation aims at extracting a dry speech signal from a recording affected by the acoustic reflections in a room. However, most current deep learning-ba…
SMITIN: Self-Monitored Inference-Time INtervention for Generative Music Transformers
Junghyun Koo, Gordon Wichern, Francois G. Germain +2
We introduce Self-Monitored Inference-Time INtervention (SMITIN), an approach for controlling an autoregressive generative music transformer using classifier probes. These simple l…
GLA-Grad: A Griffin-Lim Extended Waveform Generation Diffusion Model
Haocheng Liu, Teysir Baoueb, Mathieu Fontaine +2
Diffusion models are receiving a growing interest for a variety of signal generation tasks such as speech or music synthesis. WaveGrad, for example, is a successful diffusion model…
Latent Iterative Refinement for Modular Source Separation
Dimitrios Bralios, Efthymios Tzinis, Gordon Wichern +2
Traditional source separation approaches train deep neural network models end-to-end with all the data available at once by minimizing the empirical risk on the whole training set.…
On The Compensation Between Magnitude and Phase in Speech Separation
Zhong-Qiu Wang, Gordon Wichern, Jonathan Le Roux
Deep neural network (DNN) based end-to-end optimization in the complex time-frequency (T-F) domain or time domain has shown considerable potential in monaural speech separation. Ma…
Bootstrapping deep music separation from primitive auditory grouping principles
Prem Seetharaman, Gordon Wichern, Jonathan Le Roux +1
Separating an audio scene such as a cocktail party into constituent, meaningful components is a core task in computer audition. Deep networks are the state-of-the-art approach. The…