Sixth European Conference on Speech Communication and Technology

Budapest, Hungary
September 5-9, 1999

Using Various Language Model Smoothing Techniques for the Transcription of a Weather Forecast Broadcasted by the Czech Radio

Ludek Müller, Josef Psutka

University of West Bohemia, Department of Cybernetics, Plzen, Czech Republic

This paper presents an experimental speech recognition system used to transcribe a weather forecast broadcasted by the Czech radio. The system is based on the HMM with mixture Gaussian continuous densities and is designed as a speaker independent. To overcome very sparse training data various language models supported by smoothing of model parameters based on the leaving-one-out technique, discounting and backing-off approach were tested. The results of recognition experiments are discussed in the paper.

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Bibliographic reference.  Müller, Ludek / Psutka, Josef (1999): "Using various language model smoothing techniques for the transcription of a weather forecast broadcasted by the czech radio", In EUROSPEECH'99, 1783-1786.