'International workshop on statistical machine learning for speech processing', Kyoto, Japan
31 March 2012 - 31 March 2012
Japan
The 'International workshop on statistical machine learning for speech processing' will take place on 31 March 2012 in Kyoto, Japan.
Until recently, research in the area of statistical speech processing has been focused on high-quality data annotation and parsimonious model construction using annotated data. Attention, though, is shifting towards the issue of how to construct a model that is robust against diverse types of noise in a massive amount of data annotated with either no labels or only unreliable ones.
Within this area of research, it is often necessary to look into scalable methods that suit various amounts and quality-levels of data and domain knowledge. The workshop will bring together stakeholders in machine learning, speech, natural language, and image processing. Attendees will discuss scalable approaches in an era of abundant data as well as converting knowledge based on a massive amount of data into model constructions in different domains that have sparse data.For further information, please visit: http://www.ism.ac.jp/IWSML2012/(opens in new window)
Until recently, research in the area of statistical speech processing has been focused on high-quality data annotation and parsimonious model construction using annotated data. Attention, though, is shifting towards the issue of how to construct a model that is robust against diverse types of noise in a massive amount of data annotated with either no labels or only unreliable ones.
Within this area of research, it is often necessary to look into scalable methods that suit various amounts and quality-levels of data and domain knowledge. The workshop will bring together stakeholders in machine learning, speech, natural language, and image processing. Attendees will discuss scalable approaches in an era of abundant data as well as converting knowledge based on a massive amount of data into model constructions in different domains that have sparse data.For further information, please visit: http://www.ism.ac.jp/IWSML2012/(opens in new window)