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Source channel @githubtrending · Post #15385 · Jan 2

#python#deep_learning#inference#openai#quantization#speech_recognition#speech_to_text#transformer#whisper Faster-Whisper is a fast version of OpenAI's Whisper that transcribes audio up to 4x quicker with the same accuracy, using less memory on CPU or GPU—benchmarks show it beats original Whisper (e.g., 1m03s vs 2m23s for 13-min audio on GPU). Install via `pip install faster-whisper`, no FFmpeg needed, and use simple Python code like `WhisperModel("large-v3").transcribe("audio.mp3")` for segments with timestamps. You benefit by getting quick, efficient speech-to-text for real-time apps, saving time and resources on long files or batches. https://github.com/SYSTRAN/faster-whisper

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MessageInABottle

@mib_messageinabottle · Post #6953 · 05/26/2024, 12:59 PM

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🇬🇧#UK #PreCrime "I WAS MISIDENTIFIED AS SHOPLIFTER BY FACIAL RECOGNITION TECH" Sara needed some chocolate - she had had one of those days - so wandered into a #HomeBargains store. "Within less than a minute, I'm approached by a store worker who comes up to me and says, 'You're a thief, you need to leave the store'." Sara - who wants to remain anonymous - was wrongly accused after being flagged by a facial-recognition system called #Facewatch. She says after her bag was searched she was led out of the shop, and told she was banned from all stores using the technology. Facewatch later wrote to Sara and acknowledged it had made an error. The #MetropolitanPolice in #London say that around one in every 33,000 people who walk by its cameras is misidentified. But the error count is much higher once someone is actually flagged. One in 40 alerts so far this year has been a false positive #AI #FacialRecognition

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