In this paper, the authors present the results of ongoing research on Large Vocabulary Automatic Speech Recognition for the Latvian language. The paper describes the initial acoustic model, phoneme set, filler and noise models, and grapheme-to-phoneme modelling. The second part of this work is focused on language modelling. Different word and class-based n-gram models are evaluated in terms of perplexity and word error rate in a speech recognition task. The authors also train a recurrent neural network language model and use it for n-best rescoring.
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