Impact of variabilities on speech recognition

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 channel variability), 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. There are actually many factors affecting the speech realization: regional, sociolinguistic, or related to the environment or the speaker itself. These create a wide range of variations that may not be modeled correctly (speaker, gender, speech rate, vocal effort, regional accents, speaking style, non stationarity...), especially when resources for system training are scarce. This paper outlines some current advances related to variabilities in ASR.

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