Pierce Gerard Buckley

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In this paper, we investigate a weighted finite-state transducer approach to language modelling for speech recognition applications. We explore a unified framework to conversational speech recognition which combines the benefits of grammars, n-gram and class-based language models, with the flexibility of using dynamic data, and the potential for integrating(More)
In this paper we investigate a maximum entropy approach to spoken language understanding. We compare this approach with a parser based on finite-state transducers. The parsers are evaluated on a corpus of utterances modelling human-computer interactions within a single domain. The corpus was annotated with task-oriented semantic categories to obtain a set(More)
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