This paper describes the development of a Serbo-Croatian dictation and broadcast news speech recognizer. The intention is to generate an automatic text transcription of a news show, which will be submitted to a multilingual informedia database. We outline the complete system development process using the JanusRTk, beginning with data collection, design and training of the parameters, tuning and evaluation. We report on general recognition techniques like segmentation, adaptation and language model interpolation, as well as language specific problems, e.g. high OOV rate due to inflected word forms. We show that even with a low amount of acoustic training data, combined with Web based interpolated language models, it is sufficient to build up a fairly reliable automatic news transcription system, which yields a performance of 36.0% word error (WE).
['P. Scheytt', 'Petra Geutner', 'Alex Waibel']
Serbo-Croatian LVCSR on the dictation and broadcast news domain