02036nas a2200301   4500008004100000022001300041245006600054210006500120260001200185300001400197490000700211520125600218653000801474653001701482653001101499653002201510100001901532700001501551700001401566700001501580700001401595700001501609700001601624700001501640700001601655700001201671856005101683       2007                        eng d  a0167639300aAutomatic speech recognition and speech variability: A review0 aAutomatic speech recognition and speech variability A review  cOctober  a763–7860 v493 aMajor 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.10aasr10abioacoustics10areview10aspeechrecognition1 aBenzeghiba, M.1 aDemori, R.1 aDeroo, O.1 aDupont, S.1 aErbes, T.1 aJouvet, D.1 aFissore, L.1 aLaface, P.1 aMertins, A.1 aRis, C.  uhttp://dx.doi.org/10.1016/j.specom.2007.02.00602241nas a2200229   4500008004100000022001300041245007500054210006900129260001400198300001400212490000700226520157600233653000801809653001701817653001601834653001101850653002201861100002301883700002101906700003301927856005101960       2009                        eng d  a0167639300aTowards a neurocomputational model of speech production and perception0 aTowards a neurocomputational model of speech production and perc  cSeptember  a793–8090 v513 aThe limitation in performance of current speech synthesis and speech recognition systems may result from the fact that these systems are not designed with respect to the human neural processes of speech production and perception. A neurocomputational model of speech production and perception is introduced which is organized with respect to human neural processes of speech production and perception. The production–perception model comprises an artificial computer-implemented vocal tract as a front-end module, which is capable of generating articulatory speech movements and acoustic speech signals. The structure of the production–perception model comprises motor and sensory processing pathways. Speech knowledge is collected during training stages which imitate early stages of speech acquisition. This knowledge is stored in artificial self-organizing maps. The current neurocomputational model is capable of producing and perceiving vowels, VC-, and CV-syllables (V = vowels and C = voiced plosives). Basic features of natural speech production and perception are predicted from this model in a straight forward way: Production of speech items is feedforward and feedback controlled and phoneme realizations vary within perceptually defined regions. Perception is less categorical in the case of vowels in comparison to consonants. Due to its human-like production–perception processing the model should be discussed as a basic module for more technical relevant approaches for high-quality speech synthesis and for high performance speech recognition.10aasr10abioacoustics10alinguistics10aspeech10aspeechrecognition1 aKröger, Bernd, J.1 aKannampuzha, Jim1 aNeuschaefer-Rube, Christiane  uhttp://dx.doi.org/10.1016/j.specom.2008.08.002