Using Clinician Annotations to Improve Automatic Speech Recognition of Stuttered Speech

Peter A. Heeman, Rebecca Lunsford, Andy McMillin, J. Scott Yaruss


In treating people who stutter, clinicians often have their clients read a story in order to determine their stuttering frequency. As the client is speaking, the clinician annotates each disfluency. For further analysis of the client’s speech, it is useful to have a word transcription of what was said. However, as these are real-time annotations, they are not always correct, and they usually lag where the actual disfluency occurred. We have built a tool that rescores a word lattice taking into account the clinician’s annotations. In the paper, we describe how we incorporate the clinician’s annotations, and the improvement over a baseline version. This approach of leveraging clinician annotations can be used for other clinical tasks where a word transcription is useful for further or richer analysis.


DOI: 10.21437/Interspeech.2016-1388

Cite as

Heeman, P.A., Lunsford, R., McMillin, A., Yaruss, J.S. (2016) Using Clinician Annotations to Improve Automatic Speech Recognition of Stuttered Speech. Proc. Interspeech 2016, 2651-2655.

Bibtex
@inproceedings{Heeman+2016,
author={Peter A. Heeman and Rebecca Lunsford and Andy McMillin and J. Scott Yaruss},
title={Using Clinician Annotations to Improve Automatic Speech Recognition of Stuttered Speech},
year=2016,
booktitle={Interspeech 2016},
doi={10.21437/Interspeech.2016-1388},
url={http://dx.doi.org/10.21437/Interspeech.2016-1388},
pages={2651--2655}
}