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@@ -8,7 +8,9 @@ Demonstration paper, by Dominik Macháček, Raj Dabre, Ondřej Bojar, 2023
Abstract: Whisper is one of the recent state-of-the-art multilingual speech recognition and translation models, however, it is not designed for real time transcription. In this paper, we build on top of Whisper and create Whisper-Streaming, an implementation of real-time speech transcription and translation of Whisper-like models. Whisper-Streaming uses local agreement policy with self-adaptive latency to enable streaming transcription. We show that Whisper-Streaming achieves high quality and 3.3 seconds latency on unsegmented long-form speech transcription test set, and we demonstrate its robustness and practical usability as a component in live transcription service at a multilingual conference.
Paper in proceedings: http://www.afnlp.org/conferences/ijcnlp2023/proceedings/main-demo/cdrom/pdf/2023.ijcnlp-demo.3.pdf
Paper PDF:
https://aclanthology.org/2023.ijcnlp-demo.3.pdf
Demo video: https://player.vimeo.com/video/840442741