Architecture for text normalization using statistical machine translation techniques
| Autor: | Lopez Ludeña, Veronica, San Segundo Hernández, Rubén, Montero Martínez, Juan Manuel, Barra Chicote, Roberto, Lorenzo Trueba, Jaime |
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| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | Jornadas en Tecnología del Habla and III Iberian SLTech | VII Jornadas en Tecnología del Habla and III Iberian SLTech | 21/11/2012-22/11/2012 | Madrid, España Archivo Digital UPM Universidad Politécnica de Madrid |
| Popis: | This paper proposes an architecture, based on statistical machine translation, for developing the text normalization module of a text to speech conversion system. The main target is to generate a language independent text normalization module, based on data and flexible enough to deal with all situa-tions presented in this task. The proposed architecture is composed by three main modules: a tokenizer module for splitting the text input into a token graph (tokenization), a phrase-based translation module (token translation) and a post-processing module for removing some tokens. This paper presents initial exper-iments for numbers and abbreviations. The very good results obtained validate the proposed architecture. |
| Databáze: | OpenAIRE |
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