1 / 10

Sentence Unit Detection in Conversational Dialogue

Speaker B. Sentence Unit Detection in Conversational Dialogue. Speaker A. Prosodic features. Elizabeth Lingg , Tejaswi Tennetti , Anand Madhavan. it has a lot of garlic in it too does n't it. i it does . Sentence Units. <question>. <statement>. LDC2009T01

makan
Download Presentation

Sentence Unit Detection in Conversational Dialogue

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Speaker B Sentence Unit Detection in Conversational Dialogue Speaker A Prosodic features Elizabeth Lingg, TejaswiTennetti, Anand Madhavan it has a lot of garlic in it too does n'tit i it does Sentence Units <question> <statement>

  2. LDC2009T01 English CTS Treebank with Structural metadata Dataset used • Highlights • Fisher and Switchboard audio clips • Words annotated with POS tags • Sentence units labeled: • Question • Statement • Backchannel • Incomplete

  3. Prediction results Final results of predictions with the best features chosen

  4. Effect of POS tags

  5. Effect of special words for backchannel identification Club words like ‘mhm’, ‘oh yeah’ etc into a separate class and see if it helps in predicting backchannel better Effects on other sentence units

  6. Miscellaneous features Previous sentence class prediction (faked as well as true) Length of sentence so far or number of words so far (that have not been classified yet)

  7. Prosodic features F0 F0 normalized Pause duration for speaker Energy Length of word Pause length before word Word pitch range Energy Energy normalized

  8. Prosodic features F0 F0 normalized Pause duration for speaker Energy Length of word Pause length before word Word pitch range Energy Energy normalized

  9. Prosodic features n-gram prosodic features

  10. References Enriching Speech Recognition With Automatic Detection of Sentence Boundaries and Disfluencies, Yang Liu, Elizabeth Shriberg, Andreas Stolcke, Dustin Hillard, Mari Ostendorf and Mary Harper ...

More Related