Sixth European Conference on Speech Communication and Technology
(EUROSPEECH'99)

Budapest, Hungary
September 5-9, 1999

The Clustering Algorithm for the Definition of Multilingual Set of Context Dependent Speech Models

Bojan Imperl, Bogomir Horvat

University of Maribor, Slovenia

The paper addresses the problem of designing a language independent phonetic inventory for the speech recognisers with multilingual vocabulary. A new clustering algorithm for the definition of multilingual set of triphones is proposed. The clustering algorithm bases on a definition of a distance measure for triphones defined as a weighted sum of explicit estimates of the context similarity on a monophone level. The monophone similarity estimation method based on the algorithm of Houtgast. The clustering algorithm is integrated in a multilingual speech recognition system based on HTK V2.1.1. The ongoing experiments are based on the SpeechDat II databases 1 . So far, experiments included the Slovenian, Spanish and German 1000 FDB SpeechDat (II) database. Current results are very promising. The use of clustering algorithm resulted in a significant reduction of the number of triphones at acceptable level of word and language identification accuracy degradation.


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Bibliographic reference.  Imperl, Bojan / Horvat, Bogomir (1999): "The clustering algorithm for the definition of multilingual set of context dependent speech models", In EUROSPEECH'99, 887-890.