Automatic speech recognition and speech variability: A review

Abstract : Major progress is being recorded regularly on both the technology and exploitation of automatic speech recognition (ASR) and spoken language systems. However, there are still technological barriers to flexible solutions and user satisfaction under some circumstances. This is related to several factors, such as the sensitivity to the environment (background noise), or the weak representation of grammatical and semantic knowledge. Current research is also emphasizing deficiencies in dealing with variation naturally present in speech. For instance, the lack of robustness to foreign accents precludes the use by specific populations. Also, some applications, like directory assistance, particularly stress the core recognition technology due to the very high active vocabulary (application perplexity). There are actually many factors affecting the speech realization: regional, sociolinguistic, or related to the environment or the speaker herself. These create a wide range of variations that may not be modeled correctly (speaker, gender, speaking rate, vocal effort, regional accent, speaking style, non-stationarity, etc.), especially when resources for system training are scarce. This paper outlines current advances related to these topics.
Type de document :
Article dans une revue
Speech Communication, Elsevier : North-Holland, 2007, 〈10.1016/j.specom.2007.02.006〉
Liste complète des métadonnées

https://hal.inria.fr/inria-00616506
Contributeur : Denis Jouvet <>
Soumis le : lundi 22 août 2011 - 17:54:19
Dernière modification le : mercredi 8 novembre 2017 - 18:46:02

Identifiants

Collections

Citation

Mohamed Benzeghiba, Renato De Mori, Olivier Deroo, Stéphane Dupont, T. Erbes, et al.. Automatic speech recognition and speech variability: A review. Speech Communication, Elsevier : North-Holland, 2007, 〈10.1016/j.specom.2007.02.006〉. 〈inria-00616506〉

Partager

Métriques

Consultations de la notice

342