Spanish recognizer of continuously spelled names over the telephone

  • Authors:

  • Rubén San-Segundo;José Colás;Ricardo de Córdoba;José M. Pardo

  • Affiliations:

  • Departamento de Ingeniería Electrónica, Grupo de Tecnología del Habla, ETSI Telecomunicación, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Sp ...;Departamento de Ingeniería Electrónica, Grupo de Tecnología del Habla, ETSI Telecomunicación, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Sp ...;Departamento de Ingeniería Electrónica, Grupo de Tecnología del Habla, ETSI Telecomunicación, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Sp ...;Departamento de Ingeniería Electrónica, Grupo de Tecnología del Habla, ETSI Telecomunicación, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Sp ...

  • Venue:
  • Speech Communication
  • Year:
  • 2002

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Abstract

In this paper we present a hypothesis-verification approach for a Spanish recognizer of continuously spelled names over the telephone. We give a detailed description of the spelling task for Spanish where the most confusable letter sets are described. We introduce a new HMM topology with contextual silences incorporated into the letter model to deal with pauses between letters, increasing the Letter Accuracy by 6.6 points compared with a single silence model approach. For the final configuration of the hypothesis step we obtain a Letter Accuracy of 88.1% and a Name Recognition Rate of 94.2% for a 1000 names dictionary. In this configuration, we also use noise models for reducing letter insertions, and a Letter Graph to incorporate N-gram language models and to calculate the N-best letter sequences. In the verification step, we consider the M-best candidates provided by the hypothesis step. We evaluate the whole system for different dictionaries, obtaining more than 90.0% Name Recognition Rate for a 10,000 names dictionary. Finally, we demonstrate the utility of incorporating a Spelled Name Recognizer in a Directory Assistance Service over the telephone increasing the percentage of calls automatically serviced from 39.4% to 58.7%.