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Single Channel Speech Separation Using Source-Filter Representation

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3 Author(s)
Michael Stark ; Signal Process. & Speech Commun. Lab., Graz Univ. of Technol., Graz, Austria ; Michael Wohlmayr ; Franz Pernkopf

We propose a fully probabilistic model for source-filter based single channel source separation. In particular, we perform separation in a sequential manner, where we estimate the source-driven aspects by a factorial HMM used for multi-pitch estimation. Afterwards, these pitch tracks are combined with the vocal tract filter model to form an utterance dependent model. Additionally, we introduce a gain estimation approach to enable adaptation to arbitrary mixing levels in the speech mixtures. We thoroughly evaluate this system and finally end up in a speaker independent model.

Published in:

Pattern Recognition (ICPR), 2010 20th International Conference on

Date of Conference:

23-26 Aug. 2010