Automatic dialog acts recognition based on sentence structure

This paper deals with automatic dialog acts (DAs) recognition in Czech. Our work focuses on two applications: a multimodal reservation system and an animated talking head for hearing-impaired people. In that context, we consider the following DAs: statements, orders, investigation questions and other questions. The main goal of this paper is to propose, implement and evaluate new approaches to automatic DAs recognition based on sentence structure and prosody. Our system is tested on a Czech corpus that simulates a task of train tickets reservation. With lexical-only information, the classification accuracy is 91 %. We proposed two methods to include sentence structure information, which respectively give 94 % and 95 %. When prosodic information is further considered, the recognition accuracy reaches 96 %.

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Source IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP/2006
Author Kral, Pavel, Cerisara, Christophe, Kleckova, Jana
Maintainer CCSD
Last Updated May 14, 2026, 20:13 (UTC)
Created May 14, 2026, 20:13 (UTC)
Identifier hal-00078245
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Analysis, perception and recognition of speech (PAROLE) ; INRIA Lorraine ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)
creator Kral, Pavel
date 2006-05-14T00:00:00
harvest_object_id 01a6280e-2c43-4862-a1e9-55d471ffd8c1
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-11-04T00:00:00
set_spec type:COMM