Word segmentation through cross-lingual word-to-phoneme alignment

Felix Stahlberg, Tim Schlippe, Stephan Vogel, Tanja Schultz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

We present our new alignment model Model 3P for cross-lingual word-to-phoneme alignment, and show that unsupervised learning of word segmentation is more accurate when information of another language is used. Word segmentation with cross-lingual information is highly relevant to bootstrap pronunciation dictionaries from audio data for Automatic Speech Recognition, bypass the written form in Speech-to-Speech Translation or build the vocabulary of an unseen language, particularly in the context of under-resourced languages. Using Model 3P for the alignment between English words and Spanish phonemes outperforms a state-of-the-art monolingual word segmentation approach [1] on the BTEC corpus [2] by up to 42% absolute in F-Score on the phoneme level and a GIZA++ alignment based on IBM Model 3 by up to 17%.

Original languageEnglish
Title of host publication2012 IEEE Workshop on Spoken Language Technology, SLT 2012 - Proceedings
Pages85-90
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2012
Event2012 IEEE Workshop on Spoken Language Technology, SLT 2012 - Miami, FL, United States
Duration: 2 Dec 20125 Dec 2012

Other

Other2012 IEEE Workshop on Spoken Language Technology, SLT 2012
CountryUnited States
CityMiami, FL
Period2/12/125/12/12

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Keywords

  • alignment model
  • speech-to-speech translation
  • under-resourced language
  • word segmentation

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

Cite this

Stahlberg, F., Schlippe, T., Vogel, S., & Schultz, T. (2012). Word segmentation through cross-lingual word-to-phoneme alignment. In 2012 IEEE Workshop on Spoken Language Technology, SLT 2012 - Proceedings (pp. 85-90). [6424202] https://doi.org/10.1109/SLT.2012.6424202