Automatic speech recognition and speech variability: A review. Benzeghiba, M. F.; de Mori, R.; Deroo, O.; Dupont, S.; Erbes, T.; Jouvet, D.; Fissore, L.; Laface, P.; Mertins, A.; Ris, C.; Rose, R.; Tyagi, V.; and Wellekens, C. Speech Communication, 49(10-11):763-786.
Automatic speech recognition and speech variability: A review [link]Paper  doi  abstract   bibtex   
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.
@article{benzeghiba_automatic_2007,
	Author = {Benzeghiba, Mohamed Faouzi and de Mori, Renato and Deroo, Olivier and Dupont, Stéphane and Erbes, Teodora and Jouvet, Denis and Fissore, Luciano and Laface, Pietro and Mertins, Alfred and Ris, Christophe and Rose, Richard and Tyagi, Vivek and Wellekens, Christian},
	Date = {2007},
	Date-Modified = {2017-04-19 08:04:06 +0000},
	Doi = {10.1016/j.specom.2007.02.006},
	Journal = {Speech Communication},
	Keywords = {interspeaker variation, phonetic knowledge, speech recognition, speech technology},
	Number = {10-11},
	Pages = {763-786},
	Title = {Automatic speech recognition and speech variability: A review},
	Url = {http://dx.doi.org/10.1016/j.specom.2007.02.006},
	Volume = {49},
	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.},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.specom.2007.02.006}}
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