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2. Whisper (speech recognition system) - Wikipedia

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

   OpenAI Whisper architecture A standard Transformer architecture, showing on the left an encoder, and on the right a decoder. The Whisper architecture is based on an encoder-decoder transformer. [1] Input audio is resampled to 16,000 Hz and converting to an 80-channel log-magnitude Mel spectrogram using 25 ms windows with a 10 ms stride. The ...

3. Retrieval-based Voice Conversion - Wikipedia

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

   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.

4. 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.

5. OpenAI says it’s not using voice data or transcripts of calls ...

   www.aol.com/finance/openai-says-not-using-voice...

   And offering a free phone service to collect voice data is a tried-and-true Silicon Valley technique pioneered by Google. Google launched Google Voice Local Search, or GOOG-411, in 2007.

6. 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.

7. Transcription software - Wikipedia

   en.wikipedia.org/wiki/Transcription_software

   With speech recognition technology, transcriptionists can automatically convert recordings to text transcripts by opening recordings in a PC and uploading them to a cloud for automatic transcription, or transcribe recordings in real-time by using digital dictation. Depending on quality of recordings, machine generated transcripts may still need ...