Multilingual number transcription for text-to-speech conversion

San Segundo Hernández, Rubén and Montero Martínez, Juan Manuel and Giurgiu, M. and Muresan, I. and King, Simon (2013). Multilingual number transcription for text-to-speech conversion. In: "8th ISCA Speech Synthesis Workshop", 31/08/2013 - 02/09/2013, Barcelona, Spain. pp. 65-69.

Description

Title: Multilingual number transcription for text-to-speech conversion
Author/s:
  • San Segundo Hernández, Rubén
  • Montero Martínez, Juan Manuel
  • Giurgiu, M.
  • Muresan, I.
  • King, Simon
Item Type: Presentation at Congress or Conference (Article)
Event Title: 8th ISCA Speech Synthesis Workshop
Event Dates: 31/08/2013 - 02/09/2013
Event Location: Barcelona, Spain
Title of Book: 8th ISCA Speech Synthesis Workshop
Date: 2013
Subjects:
Freetext Keywords: Multilingual Number Transcription, text normalization, fully-trainable text conversion.
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper describes the text normalization module of a text to speech fully-trainable conversion system and its application to number transcription. The main target is to generate a language independent text normalization module, based on data instead of on expert rules. This paper proposes a general architecture based on statistical machine translation techniques. This proposal is composed of three main modules: a tokenizer for splitting the text input into a token graph, a phrase-based translation module for token translation, and a post-processing module for removing some tokens. This architecture has been evaluated for number transcription in several languages: English, Spanish and Romanian. Number transcription is an important aspect in the text normalization problem.

More information

Item ID: 30110
DC Identifier: http://oa.upm.es/30110/
OAI Identifier: oai:oa.upm.es:30110
Deposited by: Memoria Investigacion
Deposited on: 02 Aug 2014 11:13
Last Modified: 22 Apr 2016 00:25
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