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The speech-to-text industry has grown by leaps and bounds in recent years. Word error rates that once seemed remarkable are now table stakes thanks to improved training and testing techniques deployed within increasingly powerful automatic speech recognition models.
By: Migüel Jetté, VP of R&D Speech, Rev. In its nascent stages, AI may have been able to rest on the laurels of newness. It was okay for machine learning to learn slowly and maintain an opaque process where the AI’s calculation is impossible for the average consumer to penetrate. That’s changing.
The last two years have been some of the most exciting and highly anticipated in Automatic Speech Recognition’s (ASR’s) long and rich history, as we saw multiple enterprise-level fully neural network-based ASR models go to market (e.g. Alexa, Rev, AssemblyAI, ASAPP, etc).
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