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Abstract
State-of-the-art speech codecs achieve a good compromise between quality, bitrate and complexity. However, retaining performance outside the target bitrate range remains challenging. To improve performance, many codecs use pre- and post-filtering techniques to reduce the perceptual effect of quantization-noise. In this paper, we propose a postfiltering method to attenuate quantization noise which uses the complex spectral correlations of speech signals. Since conventional speech codecs cannot transmit information with temporal dependencies as transmission errors could result in severe error propagation, we model the correlation offline and employ them at the decoder, hence removing the need to transmit any side information. Objective evaluation indicates an average 4 dB improvement in the perceptual SNR of signals using the context-based post-filter, with respect to the noisy signal and an average 2 dB improvement relative to the conventional Wiener filter. These results are confirmed by an improvement of up to 30 MUSHRA points in a subjective listening test.
Original language | English |
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Title of host publication | Interspeech |
Subtitle of host publication | Annual Conference of the International Speech Communication Association |
Publisher | International Speech Communication Association (ISCA) |
Pages | 3538-3542 |
Number of pages | 5 |
DOIs | |
Publication status | Published - Sept 2018 |
MoE publication type | A4 Conference publication |
Event | Interspeech - Hyderabad International Convention Centre, Hyderabad, India Duration: 2 Sept 2018 → 6 Sept 2018 http://interspeech2018.org/ |
Publication series
Name | Interspeech |
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ISSN (Electronic) | 1990-9772 |
Conference
Conference | Interspeech |
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Country/Territory | India |
City | Hyderabad |
Period | 02/09/2018 → 06/09/2018 |
Internet address |
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Dive into the research topics of 'Postfiltering with Complex Spectral Correlations for Speech and Audio Coding'. Together they form a unique fingerprint.Projects
- 1 Finished
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Interdisciplinary research on statistical parametric speech synthesis
Alku, P. (Principal investigator), Bäckström, T. (Project Member), Juvela, L. (Project Member), Murtola, T. (Project Member), Nonavinakere Prabhakera, N. (Project Member), Bollepalli, B. (Project Member) & Airaksinen, M. (Project Member)
01/01/2018 → 31/12/2019
Project: Academy of Finland: Other research funding