Github whisper openai
WebOct 28, 2024 · The program accelerates Whisper tasks such as transcription, by multiprocessing through parallelization for CPUs. No modification to Whisper is needed. It makes use of multiple CPU cores and the results are as follows. The input file duration was 3706.393 seconds - 01:01:46(H:M:S) WebSep 23, 2024 · Thanks for sharing. There should be a section on the Whisper README to list these extensions. It is exactly what I've been looking to automate actions with voice.
Github whisper openai
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WebApr 4, 2024 · whisper-script.py. # Basic script for using the OpenAI Whisper model to transcribe a video file. You can uncomment whichever model you want to use. … WebSep 25, 2024 · Hello, I tried to replace onnx encoder and decoder instead of whisper class in model.py, and remove any part which is related to kv_cache. The output was something meaningless with lots of language tokens only. I cannot debug and found the reason. Could you please guide me how did you inference without kv_cache? Thank you.
WebNov 18, 2024 · sam1946 on Nov 20, 2024Author. In my app Whisper Memos, I use GPT-3 with the edit model: await openai.createEdit({ model: "text-davinci-edit-001", input: content, instruction: "split text into short paragraphs", temperature: 0.7, }) Forgive the basic question, but how would I get the output from Whisper (in a .txt file) to pipe into your code here? WebBuzz. Transcribe and translate audio offline on your personal computer. Powered by OpenAI's Whisper.. Buzz is better on the App Store. Get a Mac-native version of Buzz …
WebNov 9, 2024 · I developed Android APP based on tiny whisper.tflite (quantized ~40MB tflite model) Ran inference in ~2 seconds for 30 seconds audio clip on Pixel-7 mobile phone A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented as a sequence of tokens to be predicted by the … See more We used Python 3.9.9 and PyTorch 1.10.1 to train and test our models, but the codebase is expected to be compatible with Python 3.8-3.10 … See more There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. Below are the names of the available models and their approximate memory requirements and relative speed. The … See more Transcription can also be performed within Python: Internally, the transcribe()method reads the entire file and processes the audio with a sliding … See more The following command will transcribe speech in audio files, using the mediummodel: The default setting (which selects the small model) works well for transcribing English. … See more
WebOct 20, 2024 · model = whisper.load_model ("medium", 'cpu') result = model.transcribe ("TEST.mp3") result. However when I try to run it with cuda, I get this error: ValueError: Expected parameter logits (Tensor of shape (1, 51865)) of distribution Categorical (logits: torch.Size ( [1, 51865])) to satisfy the constraint IndependentConstraint (Real (), 1), but ...
WebMar 29, 2024 · Robust Speech Recognition via Large-Scale Weak Supervision - whisper/tokenizer.py at main · openai/whisper the turtles - you babyWebOct 16, 2024 · eudoxoson Oct 16, 2024. I was trying a simple. import whisper model=whisper. load_model ( "large" ) result=model. transcribe ( "p_trim3.wav") to see if I can locate timestamps for individual words/tokens in the result but I don't see them in the output. Is it possible to get this from the model? sewiousWebMar 27, 2024 · mayeaux. 1. Yes - word-level timestamps are not perfect, but it's an issue I could live with. They aren't off so much as to ruin context, and the higher quality of transcription offsets any issues. I mean, it properly transcribed eigenvalues, and other complex terms that AWS hilariously gets wrong. I'll give that PR a try. the turtle submarine museum