The ESAT 2008 System for N-Best Dutch Speech Recognition Benchmark

被引：12

作者：

Demuynck, Kris ^{[1
]}

Puurula, Antti ^{[1
]}

Van Compernolle, Dirk ^{[1
]}

Wambacq, Patrick ^{[1
]}

机构：

[1] Katholieke Univ Leuven, Dept Elect Engn, B-3001 Louvain, Belgium

来源：

2009 IEEE WORKSHOP ON AUTOMATIC SPEECH RECOGNITION & UNDERSTANDING (ASRU 2009) | 2009年

关键词：

D O I：

10.1109/ASRU.2009.5373311

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes the ESAT 2008 Broadcast News transcription system for the N-Best 2008 benchmark, developed in part for testing the recent SPRAAK Speech Recognition Toolkit. ESAT system was developed for the Southern Dutch Broadcast News subtask of N-Best using standard methods of modern speech recognition. A combination of improvements were made in commonly overlooked areas such as text normalization, pronunciation modeling, lexicon selection and morphological modeling, virtually solving the out-of-vocabulary (OOV) problem for Dutch by reducing OOV-rate to 0.06% on the N-Best development data and 0.23% on the evaluation data. Recognition experiments were run with several configurations comparing one-pass vs. two-pass decoding, high-order vs. low-order n-gram models, lexicon sizes and different types of morphological modeling. The system achieved 7.23% word error rate (WER) on the broadcast news development data and 20.3% on the much more difficult evaluation data of N-Best.

引用

页码：339 / 344

页数：6

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