This is a large wav2vec 2.0 Conformer model with rotary position embeddings (RoPE), fine-tuned on 960 hours of English speech data. Developed by Facebook AI, it achieves strong performance on automatic speech recognition tasks. The model is hosted on Hugging Face and integrates with the Transformers library for easy inference.
In the Voice, TTS & speech space, Wav2vec2 Conformer Rope Large 960h Ft takes a focused approach. High-accuracy English speech-to-text transcription using a state-of-the-art self-supervised speech model. It is built as an open-source project for developers. Wav2vec2 Conformer Rope Large 960h Ft is open source under the MIT license. It runs on the web and API.
Behind Wav2vec2 Conformer Rope Large 960h Ft is Meta, based in the United States, and the product first shipped in 2017. The GitHub repository has been archived. Key capabilities include speech recognition, conformer architecture, and fine-tuned.
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