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  2. 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.

  3. 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.

  4. Comparison of speech synthesizers - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_speech...

    Name Online demo Available language(s) Available voices Programming language Operating system(s) 15.ai: Yes English (United States) 50+ Python: Any

  5. MeCab - Wikipedia

    en.wikipedia.org/wiki/MeCab

    MeCab analyzes and segments a sentence into its parts of speech. There are several dictionaries available for MeCab, but IPADIC is the most commonly used one as with ChaSen. In 2007, Google used MeCab to generate n-gram data for a large corpus of Japanese text, which it published on its Google Japan blog. [3]

  6. BERT (language model) - Wikipedia

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

    Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1] [2] It learns to represent text as a sequence of vectors using self-supervised learning. It uses the encoder-only transformer architecture.

  7. Whisper (speech recognition system) - Wikipedia

    en.wikipedia.org/wiki/Whisper_(speech...

    Whisper is a machine learning model for speech recognition and transcription, created by OpenAI and first released as open-source software in September 2022. [2]It is capable of transcribing speech in English and several other languages, and is also capable of translating several non-English languages into English. [1]

  8. Natural Language Toolkit - Wikipedia

    en.wikipedia.org/wiki/Natural_Language_Toolkit

    Parse tree generated with NLTK. The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language.

  9. Mycroft (software) - Wikipedia

    en.wikipedia.org/wiki/Mycroft_(software)

    Mycroft was a free and open-source software virtual assistant that uses a natural language user interface. [2] [3] [4] Its code was formerly copyleft, but is now under a permissive license. [1]