Reaching over the gap: A review of efforts to link human and automatic speech recognition research

Authors:
Odette Scharenborg
Affiliations:
Speech and Hearing Research Group, Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, UK
Venue:
Speech Communication
Year:
2007

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Abstract

The fields of human speech recognition (HSR) and automatic speech recognition (ASR) both investigate parts of the speech recognition process and have word recognition as their central issue. Although the research fields appear closely related, their aims and research methods are quite different. Despite these differences there is, however, lately a growing interest in possible cross-fertilisation. Researchers from both ASR and HSR are realising the potential benefit of looking at the research field on the other side of the 'gap'. In this paper, we provide an overview of past and present efforts to link human and automatic speech recognition research and present an overview of the literature describing the performance difference between machines and human listeners. The focus of the paper is on the mutual benefits to be derived from establishing closer collaborations and knowledge interchange between ASR and HSR. The paper ends with an argument for more and closer collaborations between researchers of ASR and HSR to further improve research in both fields.