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  2. Retrieval-based Voice Conversion - Wikipedia

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

    In contrast to text-to-speech systems such as ElevenLabs, RVC differs by providing speech-to-speech outputs instead.It maintains the modulation, timbre and vocal attributes of the original speaker, making it suitable for applications where emotional tone is crucial.

  3. BLOOM (language model) - Wikipedia

    en.wikipedia.org/wiki/BLOOM_(language_model)

    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]

  4. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    models, also with Git-based version control; datasets, mainly in text, images, and audio; web applications ("spaces" and "widgets"), intended for small-scale demos of machine learning applications. There are numerous pre-trained models that support common tasks in different modalities, such as:

  5. Deep learning speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_speech_synthesis

    Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.

  6. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.

  7. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    A single-speaker, Modern Standard Arabic (MSA) speech corpus with phonetic and orthographic transcripts aligned to phoneme level. Speech is orthographically and phonetically transcribed with stress marks. ~1900 Text, WAV Speech Synthesis, Speech Recognition, Corpus Alignment, Speech Therapy, Education. 2016 [134] N. Halabi Common Voice

  8. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    GPT-2's training corpus included virtually no French text; non-English text was deliberately removed while cleaning the dataset prior to training, and as a consequence, only 10MB of French of the remaining 40,000MB was available for the model to learn from (mostly from foreign-language quotations in English posts and articles). [2]

  9. WaveNet - Wikipedia

    en.wikipedia.org/wiki/WaveNet

    WaveNet is a deep neural network for generating raw audio. It was created by researchers at London-based AI firm DeepMind.The technique, outlined in a paper in September 2016, [1] is able to generate relatively realistic-sounding human-like voices by directly modelling waveforms using a neural network method trained with recordings of real speech.

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