Implicitly Supervised Language Model Adaptation for Meeting Transcription

نویسندگان

  • David Huggins-Daines
  • Alexander I. Rudnicky
چکیده

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.

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تاریخ انتشار 2007