4th International Conference on Spoken Language Processing

Philadelphia, PA, USA
October 3-6, 1996

Automatic Acquisition of Probabilistic Dialogue Models

Kenji Kita (1), Yoshikazu Fukui (1), Masaaki Nagata (2), Tsuyoshi Morimoto (3)

(1) Faculty of Engineering, Tokushima University, Japan
(2) NTT Information and Communication Systems Laboratories, Cambridge, MA, USA
(3) ATR Interpreting Telecommunications Research Laboratories, Kyoto, Japan

In the work described here, we automatically deduce dialogue structures from a corpus with probabilistic methods. Each utterance in the corpus is annotated with a speaker label and an utterance type called IFT (Illocutionary Force Type). We use an Ergodic HMM (Hidden Markov Model) and the ALERGIA algorithm, an algorithm for learning probabilistic automata by means of state merging, to model the speaker-IFT sequences. Our experiments successfully extract typical dialogue structures such as turn-taking and speech act sequencing.

Full Paper

Bibliographic reference.  Kita, Kenji / Fukui, Yoshikazu / Nagata, Masaaki / Morimoto, Tsuyoshi (1996): "Automatic acquisition of probabilistic dialogue models", In ICSLP-1996, 196-199.