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        <title>Developing Automatic Speech Recognition for Scottish Gaelic</title>
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        <namePart type="given">Lucy</namePart>
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        <namePart type="given">Beatrice</namePart>
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            <title>Proceedings of the 4th Celtic Language Technology Workshop within LREC2022</title>
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    <abstract>This paper discusses our efforts to develop a full automatic speech recognition (ASR) system for Scottish Gaelic, starting from a point of limited resource. Building ASR technology is important for documenting and revitalising endangered languages; it enables existing resources to be enhanced with automatic subtitles and transcriptions, improves accessibility for users, and, in turn, encourages continued use of the language. In this paper, we explain the many difficulties faced when collecting minority language data for speech recognition. A novel cross-lingual approach to the alignment of training data is used to overcome one such difficulty, and in this way we demonstrate how majority language resources can bootstrap the development of lower-resourced language technology. We use the Kaldi speech recognition toolkit to develop several Gaelic ASR systems, and report a final WER of 26.30%. This is a 9.50% improvement on our original model.</abstract>
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%0 Conference Proceedings
%T Developing Automatic Speech Recognition for Scottish Gaelic
%A Evans, Lucy
%A Lamb, William
%A Sinclair, Mark
%A Alex, Beatrice
%Y Fransen, Theodorus
%Y Lamb, William
%Y Prys, Delyth
%S Proceedings of the 4th Celtic Language Technology Workshop within LREC2022
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F evans-etal-2022-developing
%X This paper discusses our efforts to develop a full automatic speech recognition (ASR) system for Scottish Gaelic, starting from a point of limited resource. Building ASR technology is important for documenting and revitalising endangered languages; it enables existing resources to be enhanced with automatic subtitles and transcriptions, improves accessibility for users, and, in turn, encourages continued use of the language. In this paper, we explain the many difficulties faced when collecting minority language data for speech recognition. A novel cross-lingual approach to the alignment of training data is used to overcome one such difficulty, and in this way we demonstrate how majority language resources can bootstrap the development of lower-resourced language technology. We use the Kaldi speech recognition toolkit to develop several Gaelic ASR systems, and report a final WER of 26.30%. This is a 9.50% improvement on our original model.
%U https://aclanthology.org/2022.cltw-1.16
%P 110-120

Markdown (Informal)

[Developing Automatic Speech Recognition for Scottish Gaelic](https://aclanthology.org/2022.cltw-1.16) (Evans et al., CLTW 2022)

• Developing Automatic Speech Recognition for Scottish Gaelic (Evans et al., CLTW 2022)

ACL

• Lucy Evans, William Lamb, Mark Sinclair, and Beatrice Alex. 2022. Developing Automatic Speech Recognition for Scottish Gaelic. In Proceedings of the 4th Celtic Language Technology Workshop within LREC2022, pages 110–120, Marseille, France. European Language Resources Association.