Skip to main content
Article thumbnail
Location of Repository

Predicting query types by prosodic analysis

By Simon Graham Jeremy Smith

Abstract

A body of work exists on the classification, by prosodic analysis and other means, of utterance types and dialogue moves in spoken corpora. Much of this output, while often linguistically well motivated, tends to rely on hand-crafted rules. This thesis presents a data-driven approach to the classification of utterances, using a novel combination of existing algorithmic approaches. Previous work has generally classified utterances according to such categories as wh- question, yes/no question, acknowledgement, response and the like; in general, the audio data used has been specially commissioned and recorded for research purposes. The work presented here departs from this tradition, in that the recorded data consists of genuine interaction between the telephone operator and members of the public. Moreover, most of the calls recorded can be characterized as queries. The techniques presented in this thesis attempt to determine, automatically, the class of query, from a set of six possibilities including "statement of a problem" and "request for action". To achieve this, a scheme for automatically labelling utterance segments according to their prosodic features was devised, and this is presented. It is then shown how labelling patterns encountered in training data can be exploited to classify unseen utterances

Topics: TK Electrical engineering. Electronics Nuclear engineering, P Philology. Linguistics
Year: 2003
OAI identifier: oai:etheses.bham.ac.uk:19

Suggested articles

Citations

  1. (2000). A Di Cristo & R Espesser
  2. (1996). Accent phrase segmentation by F0 clustering using superpositional modelling.
  3. (1988). Automatic stylization of F0 contours.
  4. (1999). Discontinuous compounds in Mandarin Chinese: a lexicalization algorithm. MSc
  5. (1967). Elements of general phonetics.
  6. (2001). Etiquetage prosodique semi-automatique de corpus oraux: algorithmes et m├ęthodologie.
  7. (2001). Speech Filing System. Available at http://www.phon.ucl.ac.uk/resource/sfs
  8. (1992). SWITCHBOARD: Telephone speech corpus for research and development.
  9. (1982). The prosodic and paralinguistic features of reading and telling stories.

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.