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Implicitly Supervised Language Model Adaptation for Meeting Transcription
Computer Science Department
  • David Huggins-Daines, Carnegie Mellon University
  • Alexander I Rudnicky, Carnegie Mellon University
Date of Original Version
Conference Proceeding
Abstract or Description
We describe the use of meeting metadata, acquired using a computerized meeting organization and note-taking system, to improve automatic transcription of meetings. By applying a two-step language model adaptation process based on notes and agenda items, we were able to reduce perplexity by 9% and word error rate by 4% relative on a set of ten meetings recorded in-house. This approach can be used to leverage other types of metadata.
Citation Information
David Huggins-Daines and Alexander I Rudnicky. "Implicitly Supervised Language Model Adaptation for Meeting Transcription" (2007)
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