Modeling Dialectal Variation for Swiss German Automatic Speech Recognition
| Type of publication: | Conference paper |
| Citation: | Khosravani_INTERSPEECH_2021 |
| Publication status: | Accepted |
| Booktitle: | Proceedings of Interspeech |
| Year: | 2021 |
| Month: | August |
| DOI: | 10.21437/Interspeech.2021-1735 |
| Abstract: | We describe a speech recognition system for Swiss German, a dialectal spoken language in German-speaking Switzerland. Swiss German has no standard orthography, with a significant variation in its written form. To alleviate the uncertainty associated with this variability, we automatically generate a lexicon from which multiple written forms of a given word in any dialect can be generated. The lexicon is built from a small (incomplete) handcrafted lexicon designed by linguistic experts and contains forms of common words in various Swiss German dialects. We exploit the powerful speech representation of self-supervised acoustic pre-training (wav2vec) to address the low-resource nature of the spoken dialects. The proposed approach results in an overall relative improvement of $9\%$ word error rate compared to one based on an expert-generated lexicon for our TV Box voice assistant application. |
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| Added by: | [UNK] |
| Total mark: | 0 |
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