But the hard stuff? That'll require humans. Sure, the machines will increasingly be able to transcribe clear and simple audio.
Problems with ai transcription how to#
Today's AI is no good at that, and AI experts are still figuring out how to engineer it. Humans disambiguate bad audio by grokking the context of the conversation, by deploying common sense. It could take a very long time to get over that hump. Background noise, cross talk, non-Western accents all tend to flummox transcription AI. Despite all the deep-learning hype, AI struggles with the messiness of reality. (Rev declined to comment on the conditions for its transcribers.)īy now you may be thinking, hey, aren't machines going to destroy all these jobs anyway? Not yet. After a few hours of intense material, “I need to have a drink-I need to smoke a joint,” Gabriel says. Many Rev transcribers have said they get none. Disturbing content is nothing new, but at an old-school firm the manager might warn a transcriber in advance. It can also be psychologically ghastly: Transcribers have opened Rev audio files to discover victims describing abuse or graphic files from police body cameras. Meanwhile, the sheer profusion of phone-recorded audio can mean that some is murky and muddled, making it mind-wracking to decipher. Humans disambiguate bad audio by grokking the context, by deploying common sense. On top of it all, AI started nipping away at the industry, with machines now able to rapidly transcribe some audio as well as humans do. Since Rev charged customers a flat rate of $1 per audio minute-less than half what transcription firms historically charged-Gabriel's pay sank even further. It has moved the industry toward an on-demand gig model.
Meanwhile, buzzy Silicon Valley startups emerged-like Rev, a sort of Uber and 800-pound gorilla of the transcription world. As audio recordings went digital and broadband spread, clients could ship work to India and the Philippines. “It was a nice life.”īut in the past decade, the bottom fell out. “I sent my son to private schools and university on transcribing,” he tells me. He'd sit at his desk, “knock it out” for hours using custom keystrokes, and watch the money roll in. In the early 2000s he'd make up to $40 an hour transcribing corporate earnings calls.
Problems with ai transcription professional#
Gabriel is a professional transcriber, and for years he earned a middle-class living.
0 kommentar(er)
