Objective
Despite good progress over the last few decades, speech recognition technology is still not sufficiently reliable for use in many real-world applications. The HIWIRE project aims to make significant improvements to the robustness, naturalness, and flexibility of vocal interaction between humans and 'machines'. The industrial partners involved in the project expect that the technological breakthrough targeted in this project will impact their future activities by:
- enabling the introduction of vocal dialogue with equipment in commercial aircraft cockpits;
- improving the potential for vocal interaction with PDAs and other mobile devices in aeronautic application environments.
It is intended that the HIWIRE project will go well beyond the current state-of-the-art for robust vocal dialogue involving large flexible vocabularies, by focusing on two main targets: improved robustness against the environment (mostly unpredictable noises like those encountered in cockpits with dense audio traffic or factory noise?) and improved tolerance to user behaviour (including speakers' vocal individuality, different accents, non-native speech, dialogue skills).
In order to guarantee common progress toward these two targets, integration nodes have been included in the project work plan (milestones M2 and M3), where the convergence toward all objectives will be verified. At these milestones, the performance will be evaluated on standard databases (for benchmarking) or on specifically collected ones for more specific issues (such as non-native speech) dialogue.
The project includes five milestones:
- M1 m10 Completion of baseline experiments on robustness;
- M2 m21 Completion of phase1 experiments on robustness;
- M3 m24 Completion of the integration of a first version of the advanced spoken dialogue system into the application platforms;
- M4 m33 Completion of phase2 experiments on robustness;
- M5 m33 Completion of evaluation on platforms.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencesdatabases
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringaircraft
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Call for proposal
Data not availableFunding Scheme
STREP - Specific Targeted Research ProjectCoordinator
33187 Le Haillan
France