Over the past thirty years, much progress has been made in the field of automatic speech recognition (ASR). Research has progressed from basic recognition tasks involving digit strings in clean environments to more demanding and complex tasks involving large vocabulary continuous speech recognition. Yet, limits exist in the ability of these speech recognition systems to perform in real-world settings. Factors such as environmental noise, changes in acoustic or microphone conditions, variation in speaker and speaking style all significantly impact speech recognition performance for today systems. Yet, while speech recognition algorithm development has progressed, so has the need to transition these working platforms to realworld applications. It is expected that ASR will dominate the humancomputer interface for the next generation in ubiquitous computing and information access.
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