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Spaiche: Extending State-of-the-Art ASR Models to Swiss German Dialects

EasyChair Preprint no. 9976

5 pagesDate: April 20, 2023


Recent breakthroughs in NLP largely increased the presence of ASR systems in our daily lives. How- ever, for many low-resource languages, ASR models still need to be improved due in part to the difficulty of acquiring pertinent data. This project aims to help advance research in ASR models for Swiss German dialects, by providing insights about the performance of state-of-the-art ASR models on recently published Swiss German speech datasets. We propose a novel loss that takes into account the semantic distance between the predicted and the ground-truth labels. We outperform current state-of-the-art results by fine-tuning OpenAI’s Whisper model on Swiss German datasets.

Keyphrases: ASR, semantics, Sentence Encoder, Swiss German dialects

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Clément Sicard and Kajetan Pyszkowski and Victor Gillioz},
  title = {Spaiche: Extending State-of-the-Art ASR Models to Swiss German Dialects},
  howpublished = {EasyChair Preprint no. 9976},

  year = {EasyChair, 2023}}
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