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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/115201...
Part of book or chapter of book . 2005 . Peer-reviewed
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DBLP
Conference object . 2017
Data sources: DBLP
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Modeling Speech Based on Harmonic Plus Noise Models

Authors: Yannis Stylianou;

Modeling Speech Based on Harmonic Plus Noise Models

Abstract

Hybrid models of speech have received increasing interest from the speech processing community. Splitting the speech signal into a periodic and a non-periodic part increases the quality of prosodic modifications necessary in concatenative speech synthesis systems. This paper focuses on the decomposition of the speech signal into a periodic and a non-periodic part based on a Harmonic plus Noise Model, HNM; three versions of HNM are discussed with respect to their effectiveness in decomposing the speech signal into a periodic and a non-periodic part. While the harmonic part is modeled explicitely, the non-periodic part (or noise part) is obtained by subtracting in the time domain the harmonic part from the original speech signal. Three versions of HNM are discussed. The objective of the discussion is to determine which of these versions could be useful for prosodic modifications and synthesis of speech.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Average
Top 10%
Top 10%
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