Does Whisper understand Swiss German? An automatic, qualitative, and human evaluation

Eyal Liron Dolev, Clemens Fidel Lutz, Noëmi Aepli
4/30/2024
cs.CL

No confident code implementation found for this paper.

Abstract

Whisper is a state-of-the-art automatic speech recognition (ASR) model (Radford et al., 2022). Although Swiss German dialects are allegedly not part of Whisper's training data, preliminary experiments showed that Whisper can transcribe Swiss German quite well, with the output being a speech translation into Standard German. To gain a better understanding of Whisper's performance on Swiss German, we systematically evaluate it using automatic, qualitative, and human evaluation. We test its performance on three existing test sets: SwissDial (Dogan-Schönberger et al., 2021), STT4SG-350 (Plüss et al., 2023), and Swiss Parliaments Corpus (Plüss et al., 2021). In addition, we create a new test set for this work, based on short mock clinical interviews. For automatic evaluation, we used word error rate (WER) and BLEU. In the qualitative analysis, we discuss Whisper's strengths and weaknesses and anylyze some output examples. For the human evaluation, we conducted a survey with 28 participants who were asked to evaluate Whisper's performance. All of our evaluations suggest that Whisper is a viable ASR system for Swiss German, so long as the Standard German output is desired.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{dolev2024does,
  title  = {Does Whisper understand Swiss German? An automatic, qualitative, and human evaluation},
  author = {Eyal Liron Dolev and Clemens Fidel Lutz and Noëmi Aepli},
  year   = {2024},
  eprint = {2404.19310},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.19310v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2404.19310.svg)](https://codeofpaper.com/paper/2404.19310)

Discussion