Human-based accent detection to assist rapid transcription with automatic speech recognition

摘要

Knowing what accent is spoken can assist automatic speech recondition (ASR) systems to more accurately transcribe audio. In one embodiment, a system includes a frontend server configured to transmit, to a backend server, an audio recording that includes speech of one or more people in a room over a period spanning at least two hours. At sonic time during the first hour of the period, the backend server provides a transcriber with a certain segment of the audio recording, and receives, from the transcriber, after the transcriber listened to a certain segment, an indication indicative of an accent of a person who spoke in the certain segment. The backend server then provides the indication to an ASR system to be utilized to generate a transcription of an additional portion of the audio recording, which was recorded after the first twenty minutes of the period.