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Perceptual Long-Term Harmonic plus Noise Modeling for Speech Data Compression

Citation Author(s):
Sonia Djaziri-Larbi
Submitted by:
Faten Ben Ali
Last updated:
23 February 2016 - 1:44pm
Document Type:
Presentation Slides
Document Year:
2015
Event:
Presenters:
Faten Ben Ali
 

The harmonic plus noise model (HNM) is widely used for the modeling of audio signals. In this paper, we introduce perceptual frequency masking to the 2-band HNM, developed by Stylianou et al., applied to speech signals. An auditory model is used to recognize inaudible sinusoids, which will be removed from the set of model’s parameters in order to reduce the data size for speech coding. The proposed perceptual HNM was applied to a large speech database from TIMIT and HINT and has proved to achieve an important (up to 50% in short term frames) parameters-rate compression, yielding a significant datarates reduction for the long-term (LT) HNM model. The latter is based on LT trajectory modeling of the Short-Term (ST) HNM parameters. Objective and subjective quality evaluation shows that the perceptual HNM introduces.

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