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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.
This is an accepted version of this page This is the latest accepted revision, reviewed on 16 November 2024. Artificial production of human speech Automatic announcement A synthetic voice announcing an arriving train in Sweden. Problems playing this file? See media help. Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech ...
ElevenLabs is primarily known for its browser-based, AI-assisted text-to-speech software, Speech Synthesis, which can produce lifelike speech by synthesizing vocal emotion and intonation. [10] The company states that its models are trained to interpret the context in the text, and adjust the intonation and pacing accordingly. [11]
Persuasive text and persuasive digital speech can be examined as AI rhetoric when the text or speech is a product or output of advanced machines that mimic human communication in some way. Historical examples of fictional artificial intelligence capable of speech are portrayed in mythology, folk tales, and science fiction. [ 1 ]
VALL-E is a generative artificial intelligence system for speech synthesis developed by Microsoft Research and announced on January 5, 2023. [1] It can "recreate any voice from a three-second sample clip". [2] It has been trained on 60,000 hours of English language speech from Meta’s audio library LibriLight. [3]
15.ai: 15: 2020 2022 Apple PlainTalk: Apple Inc. 1984 2018 ... Festival Speech Synthesis System: CSTR? 2014, December MIT-like license: FreeTTS: Paul Lamere Philip Kwok
[29] [30] [28] Tacotron2, a neural network architecture for speech synthesis developed by Google AI, was published in 2018 and required tens of hours of audio data to produce intelligible speech; when trained on 2 hours of speech, the model was able to produce intelligible speech with mediocre quality, and when trained on 36 minutes of speech ...
Retrieval-based Voice Conversion (RVC) is an open source voice conversion AI algorithm that enables realistic speech-to-speech transformations, accurately preserving the intonation and audio characteristics of the original speaker. [1]
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