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Commercial speech recognition to soon be better than human?
partnered with Center for the Study of Existential Risk, Machine Intelligence Research Institute, and The Future of Life Institute
Recently, Microsoft published a research paper detailing an experiment in speech recognition, pitting Microsoft's deep neural learning network against professional human transcribers in transcribing a recording of a conversation.
Speech recognition technology has greatly advanced in recent decades, approaching but never surpassing the same error rate as human listeners. In Microsoft's test, the neural learning system achieved a 5.9% transcribing error rate, the same as the human transcribers.
Speech recognition is not the same as speech comprehension, but the milestone signals a new era that may affect transcription software and voice controlled technology. The next question is when computer systems can recognize sounds as words better than humans.
Will commerically-available automated speech exceed human level in 2017?
This question will resolve as positive if a published research paper, corporate press release, or credible news story reports a commercially available automated speech recognition system that exceeds human accuracy on or before December 31, 2017. The claim must be based either on the commercial deployment of Microsoft's tested system, or on comparably stringent tests of a different system against skilled human transcribers.
(Edit 2/3/17 To clarify that the system need not be a Microsoft system)
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