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Source channel @githubtrending · Post #15052 · Aug 12

#python#audiobook#audiobooks#content_creation#content_creator#epub_converter#kokoro#kokoro_82m#kokoro_tts#media_generation#narrator#speech_synthesis#subtitles#text_to_audio#text_to_speech#tts#voice_synthesis Abogen is a user-friendly tool that quickly converts ePub, PDF, or text files into natural-sounding audio with synchronized subtitles, perfect for creating audiobooks or voiceovers for social media and other projects. You can customize speech speed, choose or mix voices, generate subtitles by sentence or word, and select various audio and subtitle formats. It supports batch processing with queue mode and lets you save chapters separately or merged. Installation is straightforward on Windows, Mac, and Linux, with options for GPU acceleration. This saves you time and effort in producing high-quality audio content from text files efficiently. https://github.com/denizsafak/abogen

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MessageInABottle

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

🇬🇧#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