With the distribution of speech technology products all over the world, the portability to new target languages becomes a practical concern. As a consequence our research focuses on the question of how to port LVCSR systems in a fast and efficient way. More specifically we want to estimate acoustic models for a new target language using speech data from varied source languages, but only limited data from the target language. For this purpose we introduce different methods for multilingual acoustic model combination and a polyphone decision tree specialization procedure. Recognition results using language dependent, independent and language adaptive acoustic models are presented and discussed in the framework of our GlobalPhone project which investigates LVCSR systems in 15 languages.

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A basic overview is presented of the main ongoing efforts in large vocabulary, continuous speech recognition (LVCSR) for European languages. We address issues in acoustic modeling, lexical representation, and language modeling for several European languages, as well as issues in comparative evaluation.

This thesis deals with the problem of Out-Of-Vocabulary words in speech recognition. The standard response of speech recognition systems whenever they encounter such OOV words is to (silently) misrecognize them without issuing any warning to the user. In order to avoid this undesired behaviour, two different strategies are proposed. The first strategy consists in preventing the problem, i.e. the occurrence of OOV words, and this thesis presents two ways of doing that. First, the system vocabulary is optimized using information extracted from other corpora and application domains, such that the number of expected OOV words be minimized. Using this method, the vocabulary coverage was significantly improved, especially for small vocabularies. The second method of reducing the number of OOV words consists of redefining the concept of "word" based on morphological considerations. In particular, compound words are decomposed into their constituent parts, which are used as the lexical recogni...

In this paper we describe our large vocabulary continuous speech recognition system for the German language, the development of which was partly carried out within the context of the European LRE project 62-058 Sqale. The recognition system is the LIMSI recognizer[1] originally developed for French and American English, which has been adapted to German. Specificities of German, as relevant to the recognition system, are presented. These specificities have been accounted for during the recognizer's adaptation process. We present experimental results on a first test set ger-dev95 to measure progress in system development. Results are given with the final system using different acoustic model sets on two test sets ger-dev95 and ger-eval95. This system achieved a word error rate of 17.3 % (official word error rate of 16.1 % after Sqale adjudication process) on the ger-eval95 test set. 1. INTRODUCTION Porting a speech recognizer to a new language consists mainly in the creation of the la...

This paper presents an extension of bottom-up state-tying towards improved handling of unseen triphones. As opposed to the usual backing-o# to diphones and monophones, the current method aims at #nding a triphone model that has proven to exhibit some similarity with the unseen triphone. It is based on a probabilistic mapping of unseen contexts to clusters of triphone-states observed in the training data.