Loweimi, E., Barker, J. orcid.org/0000-0002-1684-5660 and Hain, T. orcid.org/0000-0003-0939-3464 (2015) Source-filter Separation of Speech Signal in the Phase Domain. In: 16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5. Interspeech 2015, 06-10 Sep 2016, Dresden, Germany. ISCA , pp. 598-602. ISBN 978-1-5108-1790-6
Abstract
Deconvolution of the speech excitation (source) and vocal tract (filter) components through log-magnitude spectral processing is well-established and has led to the well-known cepstral features used in a multitude of speech processing tasks. This paper presents a novel source-filter decomposition based on processing in the phase domain. We show that separation between source and filter in the log-magnitude spectra is far from perfect, leading to loss of vital vocal tract information. It is demonstrated that the same task can be better performed by trend and fluctuation analysis of the phase spectrum of the minimum-phase component of speech, which can be computed via the Hilbert transform. Trend and fluctuation can be separated through low-pass filtering of the phase, using additivity of vocal tract and source in the phase domain. This results in separated signals which have a clear relation to the vocal tract and excitation components. The effectiveness of the method is put to test in a speech recognition task. The vocal tract component extracted in this way is used as the basis of a feature extraction algorithm for speech recognition on the Aurora-2 database. The recognition results shows upto 8.5% absolute improvement in comparison with MFCC features on average (0-20dB).
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 ISCA. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Speech phase spectrum; Source-filter decomposition; Hilbert transform; phase wrapping; minimum-phase component; Trend/Fluctuation analysis |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Dec 2016 15:25 |
Last Modified: | 19 Dec 2022 13:35 |
Status: | Published |
Publisher: | ISCA |
Refereed: | Yes |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109279 |