Sentence structure for dialog act recognition in Czech

This paper deals with automatic dialog acts (DAs) recognition in Czech based on sentence structure. We consider the following DAs: statements, orders, yes/no questions and other questions. In our previous works, we have proposed, implemented and evaluated new approaches to automatic DAs recognition based on sentence structure and prosody. The word sequences were manually transcribed. The main goal of this paper is to evaluate the performances of our approaches when these word sequences are unknown and estimated from a speech recognizer. Our system is tested on a Czech corpus that simulates a task of train tickets reservation. When manual transcription is used, classification accuracy without and with sentence structure models is 91 %, 94 % and 95 %. The recognition accuracy reaches 96 % with prosodic combination. When word sequences are estimated from a speech recognizer, the classification score is 88 % without and 91 % and 92 % with sentence structure models. The combination with prosody gives 93 % of accuracy.

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Additional Info

Field Value
Source 2nd IEEE International Conference on Information et Communication Technologies: from Theory to Applications - ICTTA´06
Author Kral, Pavel, Cerisara, Christophe, Kleckova, Jana, Pavelka, Tomas
Maintainer CCSD
Last Updated May 14, 2026, 20:12 (UTC)
Created May 14, 2026, 20:12 (UTC)
Identifier hal-00078247
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 3a329635-826a-4ce4-82fd-118f561fd43c
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