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Transcription of speech data with minimal manual effort

IP.com Disclosure Number: IPCOM000028925D
Original Publication Date: 2004-Jun-08
Included in the Prior Art Database: 2004-Jun-08

Publishing Venue

IBM

Abstract

Disclosed is a method to incrementally adapt the speech recognition system based on manual transcription of the speech input to reduce the amount of manual transcription required, comprising the steps of, (a) identifying sub-segments in a speech corpus, (b) adapting the speech recognition system based on the entire set of transcribed sub-segments, (c) for each sub-segment belonging to the set of yet to be transcribed sub-segments of a speech corpus, applying a speech recognition system, determining the confidence that a speech recognition system has on each sub-segments, and identifying the sub-segments on which speech recognition system has a confidence above a threshold and moving them to the set of transcribed sub-segments, (d) repeating steps (b) to (c) until a termination condition is reached, (e) selecting sub-segment(s) of the speech corpus with least confidence for manual transcription. (f) manual transcription of the identified sub-segment(s) from the speech corpus, and (g) repeating steps (b) to (f) until a termination condition is reached. The method combines unsupervised learning and supervised learning to improve the productivity of manual transcription. At the same time, active learning or dynamic selection of speech sub-segment to be manually transcribed further improves the productivity.