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Título:	Automatic alignment of long syllables in a cappella Beijing opera
Autor/a:	Dzhambazov, Georgi Bogomilov; Yang, Yile; Caro Repetto, Rafael; Serra, Xavier
Abstract:	Comunicació presentada al 6th International Workshop on Folk Music Analysis, celebrat els dies 15 a 17 de juny de 2016 a Dublín, Irlanda.
Abstract:	In this study we propose how to modify a standard approach for text-to-speech alignment to apply in the case of alignment of lyrics and singing voice. We model phoneme durations by means of a duration-explicit hidden Markov model (DHMM) phonetic recognizer based on MFCCs. The phoneme durations are empirically set in a probabilistic way, based on prior knowledge about the lyrics structure and metric principles, specific for the Beijing opera music tradition. Phoneme models are GMMs trained directly on a small corpus of annotated singing voice. The alignment is evaluated on a cappella material from Beijing opera, which is characterized by its particularly long syllable durations. Results show that the incorporation of music-specific knowledge results in a very high alignment accuracy, outperforming significantly a baseline HMM-based approach.
Abstract:	This work is partly supported by the European Research Council under the European Union’s Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583) and partly by the AGAUR research grant.
Materia(s):	-Música -- Anàlisi
Derechos:	This Conference Paper is brought to you for free and open access by the 6th International Workshop on Folk Music Analysis, 15-17 June, 2016 at ARROW@DIT. It has been accepted for inclusion in Papers by an authorized administrator of ARROW@DIT. For more information, please contact yvonne.desmond@dit.ie, arrow.admin@dit.ie, brian.widdis@dit.ie. This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License. http://creativecommons.org/licenses/by-nc-sa/3.0/
Tipo de documento:	Objeto de conferencia Artículo - Versión publicada
Editor:	International Workshop on Folk Music Analysis
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