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  2. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    On September 23, 2024, to further the International Decade of Indigenous Languages, Hugging Face teamed up with Meta and UNESCO to launch a new online language translator [14] built on Meta's No Language Left Behind open-source AI model, enabling free text translation across 200 languages, including many low-resource languages. [15]

  3. Retrieval-based Voice Conversion - Wikipedia

    en.wikipedia.org/wiki/Retrieval-Based_Voice...

    Its speed and accuracy have led many to note that its generated voices sound near-indistinguishable from "real life", provided that sufficient computational specifications and resources (e.g., a powerful GPU and ample RAM) are available when running it locally and that a high-quality voice model is used.

  4. Hugging Face cofounder Thomas Wolf says open-source AI’s ...

    www.aol.com/finance/hugging-face-cofounder...

    Interestingly, Wolf also told me Hugging Face is bucking a trend among AI companies: It's cashflow positive. (The company makes money on consulting projects and by selling tools for enterprise ...

  5. Audio deepfake - Wikipedia

    en.wikipedia.org/wiki/Audio_deepfake

    It is necessary to collect clean and well-structured raw audio with the transcripted text of the original speech audio sentence. Second, the text-to-speech model must be trained using these data to build a synthetic audio generation model. Specifically, the transcribed text with the target speaker's voice is the input of the generation model.

  6. GPT-4o - Wikipedia

    en.wikipedia.org/wiki/GPT-4o

    Sam Altman noted on 15 May 2024 that GPT-4o's voice-to-voice capabilities were not yet integrated into ChatGPT, and that the old version was still being used. [9] This new mode, called Advanced Voice Mode, is currently in limited alpha release [10] and is based on the 4o-audio-preview. [11] On 1 October 2024, the Realtime API was introduced. [12]

  7. Speech recognition - Wikipedia

    en.wikipedia.org/wiki/Speech_recognition

    The model consisted of recurrent neural networks and a CTC layer. Jointly, the RNN-CTC model learns the pronunciation and acoustic model together, however it is incapable of learning the language due to conditional independence assumptions similar to a HMM. Consequently, CTC models can directly learn to map speech acoustics to English ...