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We describe a new approach to speech recognition, in which all Hidden Markov Model (HMM) states share the same Gaussian Mixture Model (GMM) structure with the same number of Gaussians in each state. The model is defined by vectors associated with each state with a dimension of, say, 50, together with a global mapping from this vector space to the space of(More)
We describe an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure, and the means and mixture weights vary in a subspace of the total parameter space. We call this a Subspace Gaussian Mixture Model (SGMM). Globally shared parameters define the subspace. This style of acoustic model allows for a much more(More)
Although research has previously been done on multilingual speech recognition, it has been found to be very difficult to improve over separately trained systems. The usual approach has been to use some kind of “universal phone set” that covers multiple languages. We report experiments on a different approach to multilingual speech recognition,(More)
INTRODUCTION Although the relationship between risk perceptions and quit intentions has been established, few studies explore the potential impact of smoking level on these associations, and none have done so among diversely-aged samples of multiple ethnicities. METHODS Participants, ranging in age from 25 to 81, were 1133 nondaily smokers (smoked ≥1(More)
Non-specific abdominal pain (NSAP) may have a detectable psychological component that could be used to predict outcome. To test this hypothesis, 131 patients aged 14-40 years admitted with acute abdominal pain were assessed using the General Health Questionnaire (GHQ) and Hospital Anxiety and Depression (HAD) scale, and a structured interview. Of 61(More)
In this paper we present a novel approach for estimating feature-space maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maximizing the likelihood function by repeated line search in the direction of the gradient. We do this in a pre-transformed parameter space such that an approximation to the expected(More)
Preparation of a lexicon for speech recognition systems can be a significant effort in languages where the written form is not exactly phonetic. On the other hand, in languages where the written form is quite phonetic, some common words are often mispronounced. In this paper, we use a combination of lexicon learning techniques to explore whether a lexicon(More)
— through this paper we proposed the methodology that incorporates the K-means and fuzzy c means algorithm for the color image segmentation. The image segmentation may be defined as the process of dividing the given image into different parts. Here we are taking color image as the input and we are supposed to segment the given image on the basis of its(More)