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A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As such, they induce seemingly complex dependencies among the latter. In recent years, much attention has been devoted to the development of algorithms for learning parameters, and in(More)
In the present research, we explore several methods for transforming phoneme models from a language with acoustic models that have been trained (source language) to another, untrained language (target language). One approach uses acoustic distance-measures to automatically define the mapping from source to target phonemes. This is achieved by training basic(More)
Speech indexing and retrieval has become more and more crucial with the constant accumulation of massive amounts of digital data. When it comes to audio and video data, speech recognition technology is often used in Keyword Spotting (KWS) based applications to enable specific words to be identified out of a stream of continuous speech. It is commonly(More)
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