Generating segmental foreign accent

García Lecumberri, María Luisa; Barra Chicote, Roberto; Pérez Ramón, Rubén; Yamagishi, Junichi y Cooke, Martin (2014). Generating segmental foreign accent. En: "15th Annual Conference of the Internacional Speech Communication Association (Interspeech 2014)", 14/09/2014 - 18/09/2014, Singapore. pp. 1302-1306.

Descripción

Título: Generating segmental foreign accent
Autor/es:
  • García Lecumberri, María Luisa
  • Barra Chicote, Roberto
  • Pérez Ramón, Rubén
  • Yamagishi, Junichi
  • Cooke, Martin
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 15th Annual Conference of the Internacional Speech Communication Association (Interspeech 2014)
Fechas del Evento: 14/09/2014 - 18/09/2014
Lugar del Evento: Singapore
Título del Libro: 15th Annual Conference of the Internacional Speech Communication Association (Interspeech 2014)
Fecha: 2014
Materias:
Palabras Clave Informales: Foreign accent, speech synthesis, splicing
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería Electrónica
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

For most of us, speaking in a non-native language involves deviating to some extent from native pronunciation norms. However, the detailed basis for foreign accent (FA) remains elusive, in part due to methodological challenges in isolating segmental from suprasegmental factors. The current study examines the role of segmental features in conveying FA through the use of a generative approach in which accent is localised to single consonantal segments. Three techniques are evaluated: the first requires a highly-proficiency bilingual to produce words with isolated accented segments; the second uses cross-splicing of context-dependent consonants from the non-native language into native words; the third employs hidden Markov model synthesis to blend voice models for both languages. Using English and Spanish as the native/non-native languages respectively, listener cohorts from both languages identified words and rated their degree of FA. All techniques were capable of generating accented words, but to differing degrees. Naturally-produced speech led to the strongest FA ratings and synthetic speech the weakest, which we interpret as the outcome of over-smoothing. Nevertheless, the flexibility offered by synthesising localised accent encourages further development of the method.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
FP7287678SIMPLE4ALLUniversity of EdinburghSpeech synthesis that improves through adaptive learning
Gobierno de EspañaDPI2010-21247-C02-02Sin especificarSin especificarSin especificar

Más información

ID de Registro: 37539
Identificador DC: http://oa.upm.es/37539/
Identificador OAI: oai:oa.upm.es:37539
Depositado por: Memoria Investigacion
Depositado el: 20 Oct 2015 15:51
Ultima Modificación: 06 Jun 2016 15:51
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