mlsanityData to 7 Oct 2026

Scribosermo: Fast Speech-to-Text models for German and other Languages

arXiv 2110.07982 ↗First posted 15 Oct 2021cs.CL cs.SD eess.AScited by 7

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Abstract (arXiv)

Recent Speech-to-Text models often require a large amount of hardware resources and are mostly trained in English. This paper presents Speech-to-Text models for German, as well as for Spanish and French with special features: (a) They are small and run in real-time on microcontrollers like a RaspberryPi. (b) Using a pretrained English model, they can be trained on consumer-grade hardware with a relatively small dataset. (c) The models are competitive with other solutions and outperform them in German. In this respect, the models combine advantages of other approaches, which only include a subset of the presented features. Furthermore, the paper provides a new library for handling datasets, which is focused on easy extension with additional datasets and shows an optimized way for transfer-learning new languages using a pretrained model from another language with a similar alphabet.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 9 of its 51 references that are in the map. First posted on arXiv 15 Oct 2021.

Builds on

9 of 51 references.

References · 9

  1. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
  2. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,358
  3. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 455
  4. 2018Streaming End-to-end Speech Recognition For Mobile Devicescited by 230
  5. 2021The Multilingual TEDx Corpus for Speech Recognition and Translationcited by 101
  6. 2019QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutionscited by 93
  7. 2019CSS10: A Collection of Single Speaker Speech Datasets for 10 Languagescited by 54
  8. 2021Tiny Transducer: A Highly-efficient Speech Recognition Model on Edge Devicescited by 18
  9. 2019IMS-Speech: A Speech to Text Toolcited by 4

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Cited by year

Citing papers per year: 2022: 4; 2023: 1; 2024: 1; 2025: 1.

7 papers.