Automated Speech Recognition: A Framework for Research

AUTOMATED SPEECH RECOGNITION: A FRAMEWORK FOR RESEARCH Anne Johnstone Department of Artificial Intelligence Edinburgh University Hope Park Square, Meadow Lane Edinburgh EHB 9LL. (GB) ABSTRACT This paper reflects the view that the decoding of speech, either by computer systems or people, must to a large extent be determined by the ways in which the speaker has encoded the information necessary for its comprehension. We therefore place great emphasis on the use of psycholinguistics as a tool for the construction of models essential to the characterisation of the speech understanding task. We are primarily concerned with the interactions between the various levels at which a fragment of speech can be described (e.g. acoustic-phonetic, lexical, syntactic, etc), and the ways in which the knowledge bases associated with each of these "levels" contribute towards a final interpretation of an utterance. We propose to use the Chart Parser as a general computational framework for simulating such interactions, since its flexibility allows various models to be implemented and evaluated. Within this general framework we discuss problems of information flow and search strategy in combining evidence across levels of description and across time, during the extension of an hypothesis. We stress the importance of both psychological and computational theory in developing a particular control strategy which could be implemented within the framework. Introduction The decoding of speech, either by computer systems or people, must to a large extent be determined by the ways in which the speaker has encoded the information necessary for its comprehension. Such a view is supported by a large body of experimental evidence concerning the ways in which various factors (eg. predictability from context) affect both the acoustic clarity with which a speaker pronounces an utterance, and the strategy the hearer appears to use in identifying it. The task of the Gerry Altmann Department of Linguistics Edinburgh University George Square Edinburgh EHB 9LL. (GB) compu-£er system is to mimic, though preferably model, this strategy. In order to do so, one should presumably draw on both computational and psychological theories of process. Such a dual approach has been shown to be feasible, and indeed desirable, by research into early visual processing (eg. Marr 1976) which has shown that there can come a point when psychological and computational descriptions become barely distinguishable. This analogy with early visual processing is significant because central to the development of the vision research was the notion of 'modelling': one can argue that a significant difference between the so-called '4th Generation' and '5th Genera£ion' technologies is that with the former ad- hoc algorithms are applied to often incomplete and unreliable data, while with 5th Generation systems, algorithms are devised by first constructing qualitative models suited to the task domain. We propose to use psycholinguistics as a tool for the construction of models essential to the characterisation of the speech understanding task. We believe that this approach is essential to the development of automated speech recognition systems, and will also prove beneficial to psychological models of human speech processing, the …

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