Nearest neighbor approach in speaker adaptation for HMM-based speech synthesis

Name: Nearest neighbor approach in speaker adaptation for HMM-based speech synthesis
Author: Mohammadi, Amir, Demiroğlu, Cenk

İsim	Nearest neighbor approach in speaker adaptation for HMM-based speech synthesis
Yazar	Mohammadi, Amir, Demiroğlu, Cenk
Basım Tarihi:	2013
Basım Yeri	- IEEE
Konu	Hidden Markov models, Speech synthesis, Statistical analysis
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-4673-5561-2
Kayıt Numarası	91f5927c-3b2b-4bf1-bc3a-7f5fb8146274
Lokasyon	Electrical & Electronics Engineering
Tarih	2013
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	Statistical speech synthesis (SSS) approach has become one of the most popular and successful methods in the speech synthesis field. Smooth speech transitions, without the spurious errors that are observed in unit selection systems, can be generated with the SSS approach. Another advantage is the ability to adapt to a target speaker with a couple of minutes of adaptation data. However, many applications, especially in consumer electronics, require adaptation with only a few adaptation utterances. Here, we propose a rapid adaptation technique that first attempt to select a reference model that is close to the target speaker given a distance measure. Then, as opposed to adapting to target speaker from an average model, as typically done in most systems, adaptation is performed from the new reference model. The proposed system significantly outperformed a state-of-the-art baseline system both in objective and subjective tests especially only when one utterance is available for adaptation.
DOI	10.1109/SIU.2013.6531576

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Nearest neighbor approach in speaker adaptation for HMM-based speech synthesis

Yazar Mohammadi, Amir, Demiroğlu, Cenk

Basım Tarihi 2013

Basım Yeri - IEEE

Konu Hidden Markov models, Speech synthesis, Statistical analysis

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-4673-5561-2

Kayıt Numarası 91f5927c-3b2b-4bf1-bc3a-7f5fb8146274

Lokasyon Electrical & Electronics Engineering

Tarih 2013

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin Statistical speech synthesis (SSS) approach has become one of the most popular and successful methods in the speech synthesis field. Smooth speech transitions, without the spurious errors that are observed in unit selection systems, can be generated with the SSS approach. Another advantage is the ability to adapt to a target speaker with a couple of minutes of adaptation data. However, many applications, especially in consumer electronics, require adaptation with only a few adaptation utterances. Here, we propose a rapid adaptation technique that first attempt to select a reference model that is close to the target speaker given a distance measure. Then, as opposed to adapting to target speaker from an average model, as typically done in most systems, adaptation is performed from the new reference model. The proposed system significantly outperformed a state-of-the-art baseline system both in objective and subjective tests especially only when one utterance is available for adaptation.

DOI 10.1109/SIU.2013.6531576