activity
20162025
most citedPoCoNet: Better Speech Enhancement with Frequency-Positional Embeddings, Semi-Supervised Conversational Data, and Biased Loss

6 citations · 10 across the 11 of their papers we have counts for

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10 papers · 1 filter

cs.SD2016

Channel Decorrelation For Stereo Acoustic Echo Cancellation In High-Quality Audio Communication

Jean-Marc Valin

In this paper, we address an important problem in high-quality audio communication systems. Acoustic echo cancellation with stereo signals is generally an under-determined problem…

cs.SD2016

Microphone array post-filter for separation of simultaneous non-stationary sources

Jean-Marc Valin, Jean Rouat, François Michaud

Microphone array post-filters have demonstrated their ability to greatly reduce noise at the output of a beamformer. However, current techniques only consider a single source of in…

cs.SD2016

Improved Noise Weighting in CELP Coding of Speech - Applying the Vorbis Psychoacoustic Model To Speex

Jean-Marc Valin, Christopher Montgomery

One key aspect of the CELP algorithm is that it shapes the coding noise using a simple, yet effective, weighting filter. In this paper, we improve the noise shaping of CELP using a…

cs.SD2016

Low-Complexity Iterative Sinusoidal Parameter Estimation

Jean-Marc Valin, Daniel V. Smith, Christopher Montgomery +1

Sinusoidal parameter estimation is a computationally-intensive task, which can pose problems for real-time implementations. In this paper, we propose a low-complexity iterative met…

cs.SD2016

Speex: A Free Codec For Free Speech

Jean-Marc Valin

The Speex project has been started in 2002 to address the need for a free, open-source speech codec. Speex is based on the Code Excited Linear Prediction (CELP) algorithm and, unli…

cs.SD2016

Perceptually-Motivated Nonlinear Channel Decorrelation For Stereo Acoustic Echo Cancellation

Jean-Marc Valin

Acoustic echo cancellation with stereo signals is generally an under-determined problem because of the high coherence between the left and right channels. In this paper, we present…