This open-source wav2vec2 model performs automatic speech recognition for Chinese audio, specifically the zh-CN language variant. Developers and researchers can load it with Transformers, run it locally, or deploy it through compatible inference services.
Wav2vec2 Large Xlsr 53 Chinese Zh Cn sits in PulseGate's Speech to text category. It focuses on transcribing Chinese speech into text without building an automatic speech recognition model from scratch. It is built as an open-source project for machine learning developers and speech researchers. The project is open source (Apache-2.0). It runs on the web and API, and it can be self-hosted.
Behind Wav2vec2 Large Xlsr 53 Chinese Zh Cn is Jonatas Grosman, and it first shipped in 2018. Development happens publicly on GitHub with 491 stars. PulseGate's similarity index places it among 15 comparable projects. Among its 8 catalogued features are automatic transcription, chinese zh-CN support, and transformers integration.
Summary written by a language model from the project’s public pages.
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