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Progress of Interspeech 2005 Information Line

Progress of Interspeech 2005 Information Line. By Team Infoline April 24, 2006. Speech Recognizer and Robust Parser. Speech Recognizer Challenging Situation No Training data, Names are there. Temp Solution New Language Model is trained based on generated corpora

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Progress of Interspeech 2005 Information Line

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  1. Progress of Interspeech 2005 Information Line By Team Infoline April 24, 2006

  2. Speech Recognizer and Robust Parser • Speech Recognizer • Challenging Situation • No Training data, • Names are there. • Temp Solution • New Language Model is trained based on generated corpora • Significantly trimmed down the number of authors to recognize (From 200 to 30) • Few author names are easily recognized still. • Robust Parser • Loosen up to deal with irregularities of SR output

  3. DM • Allow disambiguation using author name and session name • Taken care of different scenarios of results • If there is no results, • Say Sorry and restart. • If there is one result • Present the detail of the paper, • Then ask whether to present the abstract of the paper • If there is less than or equal to 5 results • Tell the user the number of papers found • Then ask whether to present the summary of the paper. • (List of titles of the paper) • If there is more than 5 results • Say sorry

  4. Backend and NLG • Backend • (may be for this demo only) • SQL-based • Could do author-search and session-name-search • NLG • Fill in all sorts of prompts • A lot of Implicit Confirmation and Explicit Confirmation are missing • That caused a lot of “” in the system

  5. Other small things We Hacked Out • Confidence of The Recognizer • Audio Server is hacked such that • We are always “confident” about the results. • Annoying restarting issue • Commented the restarting routine in Windows • Speech Rec (We really fixed these) • SVQ could now be used. • Memory reallocation is fixed

  6. Demo • Scenario • A user want to know the papers written by • Alan Black • Julia Hirschberg and • Andrew Rosenberg • What it shows • How bad recognition is taken care now. • What happened when the number of answers returned are multiple or single.

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