Jiang, PP;
Tobin, J;
Tomanek, K;
MacDonald, RL;
Seaver, K;
Cave, R;
Ladewig, M;
... Green, JR; + view all
(2024)
Learnings from curating a trustworthy, well-annotated, and useful dataset of disordered English speech.
In:
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH.
(pp. pp. 2490-2493).
ISCA - International Speech Communication Association
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Abstract
Project Euphonia, a Google initiative, is dedicated to improving automatic speech recognition (ASR) of disordered speech. A central objective of the project is to create a large, high-quality, and diverse speech corpus. This report describes the project's latest advancements in data collection and annotation methodologies, such as expanding speaker diversity in the database, adding human-reviewed transcript corrections and audio quality tags to 350K (of the 1.2M total) audio recordings, and amassing a comprehensive set of metadata (including more than 40 speech characteristic labels) for over 75% of the speakers in the database. We report on the impact of transcript corrections on our machine-learning (ML) research, inter-rater variability of assessments of disordered speech patterns, and our rationale for gathering speech metadata. We also consider the limitations of using automated off-the-shelf annotation methods for assessing disordered speech.
| Type: | Proceedings paper |
|---|---|
| Title: | Learnings from curating a trustworthy, well-annotated, and useful dataset of disordered English speech |
| Event: | Annual Conference of the International Speech Communication Association, INTERSPEECH 2024 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.21437/Interspeech.2024-578 |
| Publisher version: | https://doi.org/10.21437/interspeech.2024-578 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10203956 |
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