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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. ElevenLabs - Wikipedia

   en.wikipedia.org/wiki/ElevenLabs

   The feature is capable of preserving the speaker's original voice, emotions, and intonation, by employing proprietary methods to handle tasks like noise removal, speaker differentiation, transcription, and synchronization of translated speech with the original audio. [19] In May 2024, ElevenLabs launched a text-to-music model. [20]

4. Speech synthesis - Wikipedia

   en.wikipedia.org/wiki/Speech_synthesis

   A text-to-speech system (or "engine") is composed of two parts: [3] a front-end and a back-end. The front-end has two major tasks. First, it converts raw text containing symbols like numbers and abbreviations into the equivalent of written-out words. This process is often called text normalization, pre-processing, or tokenization.

5. AOL Mail

   mail.aol.com

   Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

6. List of speech recognition software - Wikipedia

   en.wikipedia.org/wiki/List_of_speech_recognition...

   This initial version already contained Direct Speech Recognition and Direct Text To Speech APIs which applications could use to directly control engines, as well as simplified 'higher-level' Voice Command and Voice Talk APIs.

7. 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.