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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 ...
That warning hasn’t stopped hospitals or medical centers from using speech-to-text models, including Whisper, to transcribe what’s said during doctor’s visits to free up medical providers to ...
Speech recognition remains a challenging problem in AI and machine learning. In a step toward solving it, OpenAI today open-sourced Whisper, an automatic speech recognition system that the company ...
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.
Before llama.cpp, Gerganov worked on a similar library called whisper.cpp which implemented Whisper, a speech to text model by OpenAI. [9] Gerganov has a background in medical physics, and was part of the Faculty of Physics in Sofia University. [10] In 2006 he won a silver medal in the International Physics Olympiad.
Older generations of Nokia phones like Nokia N Series (before using Windows 7 mobile technology) used speech-recognition with family names from contact list and a few commands. Siri , originally implemented in the iPhone 4S , Apple's personal assistant for iOS , which uses technology from Nuance Communications .
eSpeak is a free and open-source, cross-platform, compact, software speech synthesizer.It uses a formant synthesis method, providing many languages in a relatively small file size. eSpeakNG (Next Generation) is a continuation of the original developer's project with more feedback from native speakers.
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.
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