Reverb: Open-Source ASR and Diarization from Rev
Nishchal Bhandari, Danny Chen, Miguel \'Angel del R\'io Fern\'andez,, Natalie Delworth, Jennifer Drexler Fox, Mig\"uel Jett\'e, Quinten McNamara,, Corey Miller, Ond\v{r}ej Novotn\'y, J\'an Profant, Nan Qin, Martin Ratajczak,, and Jean-Philippe Robichaud

TL;DR
Reverb provides open-source speech recognition and diarization models, including a full pipeline and research versions, aiming to accelerate innovation and outperform existing open-source models in long-form speech tasks.
Contribution
It introduces open-source, high-performance speech recognition and diarization models with both production and research versions for the first time.
Findings
Models outperform all existing open-source speech recognition models.
Reverb enables research and development in voice technology.
Open-source release encourages community-driven innovation.
Abstract
Today, we are open-sourcing our core speech recognition and diarization models for non-commercial use. We are releasing both a full production pipeline for developers as well as pared-down research models for experimentation. Rev hopes that these releases will spur research and innovation in the fast-moving domain of voice technology. The speech recognition models released today outperform all existing open source speech recognition models across a variety of long-form speech recognition domains.
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Taxonomy
TopicsNatural Language Processing Techniques
