Abstract
This paper presents a next-generation web application that enables users to contribute corrections to automatically acquired transcription of long speech recordings. We describe differences from similar settings, compare our solution with others and reflect on the development from the now 6 years old work we build upon in the light of the progress made, lessons learned and the new technologies available in the browser.
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Notes
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Transcriber explicitly aligns the text with speech, while the other two merely support addition of timestamps into the transcription.
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Transcribe supports team co-operation.
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In our data, other speakers represent a negligible fraction but we may later add support for speaker annotation.
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The current word is on the top line on the screenshot because it is at the beginning of the recording.
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The median number of chunks is 1 (most recordings have no manually corrected segments), maximum is 1109. Median only counting touched recordings is 8.
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We could even stop the recalculation as soon as we find that the new horizontal coordinate of a word is left untouched, and add the difference in the vertical coordinate to all subsequent words, i.e. when a line stays the same, so do all below it.
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Acknowledgments
The research was supported by SVV project number 260 453. This work has been using language resources stored and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).
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Krůza, O., Kuboň, V. (2019). Second-Generation Web Interface to Correcting ASR Output. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Proceedings of the Future Technologies Conference (FTC) 2018. FTC 2018. Advances in Intelligent Systems and Computing, vol 880. Springer, Cham. https://doi.org/10.1007/978-3-030-02686-8_56
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