Multilingual Vocabularies in Automatic Speech Recognition

Abstract

The paper describes a method for dealing with multilingual vocabularies in speech recognition tasks. We present an approach that combines acoustic descriptive precision and capability of generalization to multiple languages. The approach is based on the concept of classes of transitions between phones. The classes are defined by means of objective measures on acoustic similarities among sounds of different languages. This procedure stems from the definition of a general language-independent model. When a new language is to be added, the phonological structure of the language is mapped onto the set of classes belonging to the general model. Successively, if a limited amount of language-specific speech data becomes available for the new language, we identify those sounds which require the definition of additional classes. The experiments have been conducted in Italian, English and Spanish languages. The method can also be considered as a way of implementing cross-lingual porting of recognition models for a rapid prototyping of recognizers in a new target language, specifically in cases whereby the collection of large training databases would be economically infeasible.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2000
Accession Number
ADP010389

Entities

People

  • Alessandra Frasca
  • Enrico Palme
  • Giorgio Micca

Tags

DTIC Thesaurus Topics

  • Automated Speech Recognition
  • Databases
  • Hidden Markov Models
  • Identification
  • Inventory
  • Italian Language
  • Language
  • Markov Models
  • Models
  • Precision
  • Product Prototyping
  • Recognition
  • Software Prototyping
  • Spanish Language
  • Training
  • Transitions
  • Vocabulary

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Translation
  • AI & ML - Neural Networks