Evaluation of alternatives on speech to sign language translation

نویسندگان

  • Rubén San-Segundo-Hernández
  • Alicia Pérez
  • Daniel Ortiz-Martínez
  • Luis Fernando D'Haro
  • M. Inés Torres
  • Francisco Casacuberta
چکیده

This paper evaluates different approaches on speech to sign language machine translation. The framework of the application focuses on assisting deaf people to apply for the passport or related information. In this context, the main aim is to automatically translate the spontaneous speech, uttered by an officer, into Spanish Sign Language (SSL). In order to get the best translation quality, three alternative techniques have been evaluated: a rule-based approach, a phrase-based statistical approach, and a approach that makes use of stochastic finite state transducers. The best speech translation experiments have reported a 32.0% SER (Sign Error Rate) and a 7.1 BLEU (BiLingual Evaluation Understudy) including speech recognition errors.

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تاریخ انتشار 2007