Implementing Easy-to-Use Recipes for the Switchboard Benchmark

  • We report on our contribution of templates for tokenization, language modeling, and automatic speech recognition (ASR) on the Switchboard benchmark to the open-source general-purpose toolkit SpeechBrain. Three recipes for the training of end-to-end ASR systems were implemented. We describe their model architectures, as well as the necessary data preparation steps. The word error rates achievable with our models are comparable to or better than those of other popular toolkits. Pre-trained ASR models were made available on HuggingFace. They can be easily integrated into research projects or used directly for quick inference via a hosted inference API.

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Metadaten
Author:Dominik Wagner, Sebastian P. BayerlORCiD, Tobias Bocklet, Christoph Draxler
Publisher:TUDpress, Dresden
Document Type:conference proceeding (article)
Language:English
Reviewed:Begutachtet/Reviewed
Release Date:2024/07/03
Pagenumber:8
First Page:150
Last Page:157
Konferenzangabe:Elektronische Sprachsignalverarbeitung 2023
institutes:Fakultät Informatik
Licence (German):Keine Lizenz - Deutsches Urheberrecht gilt
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