Abstract
This paper describes a method of ASR (automatic speech recognition) engine independent error correction for a dialog system. The proposed method can correct ASR errors only with a text corpus which is used for training of the target dialog system, and it means that the method is independent of the ASR engine. We evaluated our method on two test corpora (Korean and English) that are parallel corpora including ASR results and their correct transcriptions. Overall results indicate that the method decreases the word error rate of the ASR results and recovers the errors in the important attributes of the dialog system. The method is general and can also be applied to the other speech based applications such as voice question-answering and speech information extraction systems.
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Notes
- 1.
Most of the commercial ASR engine is provided as a whole system in binary code.
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Acknowledgments
This work was partly supported by the IT R&D program of MSIP/KEIT [10044508, Development of Non-Symbolic Approach-based Human-Like-Self-Taught Learning Intelligence Technology] and by the Quality of Life Technology (QoLT) development program of MKE [10036458, Development of Voice Word-processor and Voice-controlled Computer Software for Physical Handicapped Person].
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Choi, J. et al. (2016). Engine-Independent ASR Error Management for Dialog Systems. In: Rudnicky, A., Raux, A., Lane, I., Misu, T. (eds) Situated Dialog in Speech-Based Human-Computer Interaction. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-21834-2_17
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DOI: https://doi.org/10.1007/978-3-319-21834-2_17
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