Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
5 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A Variational EM Algorithm for the Separation of Time-Varying Convolutive Audio Mixtures (1510.04595v3)

Published 15 Oct 2015 in cs.SD

Abstract: This paper addresses the problem of separating audio sources from time-varying convolutive mixtures. We propose a probabilistic framework based on the local complex-Gaussian model combined with non-negative matrix factorization. The time-varying mixing filters are modeled by a continuous temporal stochastic process. We present a variational expectation-maximization (VEM) algorithm that employs a Kalman smoother to estimate the time-varying mixing matrix, and that jointly estimate the source parameters. The sound sources are then separated by Wiener filters constructed with the estimators provided by the VEM algorithm. Extensive experiments on simulated data show that the proposed method outperforms a block-wise version of a state-of-the-art baseline method.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Dionyssos Kounades-Bastian (2 papers)
  2. Laurent Girin (40 papers)
  3. Xavier Alameda-Pineda (69 papers)
  4. Sharon Gannot (47 papers)
  5. Radu Horaud (70 papers)
Citations (43)

Summary

We haven't generated a summary for this paper yet.