As per benchmarks published in March 2020, Amazon had an accuracy of 73% (i.e., 27% WER), Microsoft was 78% accurate, Google came in at 79%, and Rev.ai (a dedicated speech-to-text engine provider) scored a slightly better 84%. Surprisingly, despite the sophisticated nature of A I today, the average WER for speech-to-text is far from 100%. Either way, knowing a speech-to-text engine’s WER is essential to understanding how reliable it actually is. Technically, accuracy is the exact inverse of WER if a piece of transcribed text contains 2% of errors, then it means that it is 98% accurate. This is measured in Word Error Rate (WER) which is the percentage of errors for every 100 words. The relia bility of speech-to-text hinges on its accuracy rate – i.e., how many errors it would contain on an average. But there is a catch here – how reliable is speech-to-text, really? The State of Speech-to-Text Accuracy in 2021įirst, let’s understand how speech-to-text accuracy is measured. Speech to text works with live audio and recorded files equally well, aiming to give you accurate transcripts that you can use for sentiment analysis, quality assurance, and agent training. Speech-to-text technology uses artificial intelligence (AI) to automatically transcribe raw speech into structured written text.

Chinese speech to text software