N-Best 2008: A Benchmark Evaluation for Large Vocabulary Speech Recognition in Dutch
David A. van Leeuwen · Theory and applications of natural language processing · 2012
In 2008 an evaluation of large vocabulary continuous speech recognition systems for the Dutch language was conducted. The tasks consisted of transcription of Broadcast News and Conversational Telephone Speech in the Northern and Southern regional language variants (Dutch and Flemish). The evaluation was modeled after the well known ARPA/NIST evaluations and the French Technolangue Evalda campaigns. This paper reviews the tasks and evaluation methodology used, presents the official results and discusses some additional analyses. Acoustic and textual training material was specified and provided in a primary evaluation condition. Seven academic sites from four European countries submitted results to this evaluation in four primary transcription tasks. The best results reported are a word error rate of 15.9% for Southern Dutch Broadcast News. Text normalisation, vocabulary and pronunciation modeling are common among the important system development efforts. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.