Source-Filter Model Based Single Channel Speech Separation (2010)
Abstract / truncated to 115 words
In a natural acoustic environment, multiple sources are usually active at the same time. The task of source separation is the estimation of individual source signals from this complex mixture. The challenge of single channel source separation (SCSS) is to recover more than one source from a single observation. Basically, SCSS can be divided in methods that try to mimic the human auditory system and model-based methods, which ﬁnd a probabilistic representation of the individual sources and employ this prior knowledge for inference. This thesis presents several strategies for the separation of two speech utterances mixed into a single channel and is structured in four parts: The ﬁrst part reviews factorial models in model-based SCSS ... toggle 6 keywordssource separation – single channel speech separation – factorial models – gaussian mixture models – gain-shape model – iterated conditional modes algorithm
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