Mark Farrell

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A recent trial of natural language call steering on live UK calls to the operator is described along with its results. The characteristics of the problem are described along with the acoustic, language, semantic and dialogue modelling approaches employed. Natural language call steering is found to be viable, with recognition and semantic accuracy the(More)
In this paper, a dialogue system for natural language based call steering is described and studied. The system is based on natural language speech recognition and understanding within a mixed initiative dialogue. The system is implemented on Bell Labs. Speech Technology Integration Platform (BLSTIP) using dialogue and natural language understanding(More)
" How may I help you? " systems where a caller to a call centre is routed to one of a set of destinations using machine recognition of spontaneous natural language is a difficult task. Previous BT " How May I Help You " work [1,2] has used top 1 recognition results for classification with much better results when tested on human transcriptions. Classifying(More)
This paper compares two noise compensation techniques for increasing recognition performance on tone corrupted speech from payphones. An analysis of payphone speech is made which identifies two harmful processes-signalling tones and increased background noise. The techniques of spectral subtraction and parallel model combination are compared on this task(More)
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