Automatic speech recognition and speech variability: A review

Publication Type:Journal Article
Year of Publication:2007
Authors:Benzeghiba, M, Demori, R, Deroo, O, Dupont, S, Erbes, T, Jouvet, D, Fissore, L, Laface, P, Mertins, A, Ris, C
Journal:Speech Communication
Volume:49
Pagination:763–786
Date Published:October
ISSN:01676393
Keywords:asr, bioacoustics, review, speechrecognition
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.

URL:http://dx.doi.org/10.1016/j.specom.2007.02.006
DOI:10.1016/j.specom.2007.02.006
Scratchpads developed and conceived by (alphabetical): Ed Baker, Katherine Bouton Alice Heaton Dimitris Koureas, Laurence Livermore, Dave Roberts, Simon Rycroft, Ben Scott, Vince Smith