Using Language Modelling to Integrate Speech Recognition with a Flat Semantic Analysis
Dirk Büler, Wolfgang Minker, Artha Elciyanti · 2005
One-stage decoding as an integration of speech recognition and linguistic analysis into one probabilistic process is an interesting trend in speech research.In this paper, we present a simple one-stage decoding scheme that can be realised without the implementation of a specialized decoder, nor the use of complex language models.Instead, we reduce an HMMbased semantic analysis to the problem of deriving annotated versions of the conventional language model, while the acoustic model remains unchanged.We present experiments with the ATIS corpus (Price, 1990) in which the performance of the one-stage method is shown to be comparable with the traditional two-stage approach, while requiring a significantly smaller increase in language model size.