Improved Phone Posterior Estimation Through k-NN and MLP-Based Similarity
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is presented. The system has no {\it a priori} knowledge of passwords. A hybrid HMM/ANN system is used to infer the phonetic transcription of the password. The emission probabilities are then modeled by a multi-Gaussians HMM model. Evaluation experiments, ...
This paper presents a cursive character recognizer embedded in an off-line cursive script recognition system. The recognizer is composed of two modules: the first one is a feature extractor, the second one an LVQ. The selected feature set was compared to Z ...
We define multi-scale moments that are estimated locally by analyzing the image through a sliding window at multiple scales. When the analysis window satisfies a two-scale relation, we prove that these moments can be computed very efficiently using a multi ...
We prove that the pointwise inequality used by P. Hajlasz in his definition of Sobolev spaces on metric spaces is equivalent to an integral (Poincaré-type) inequality. ...
HMM2 is a particular hidden Markov model where state emission probabilities of the temporal (primary) HMM are modeled through (secondary) state-dependent frequency-based HMMs [12]. As shown in [13], a secondary HMM can also be used to extract robust ASR fe ...
HMM2 is a particular hidden Markov model where state emission probabilities of the temporal (primary) HMM are modeled through (secondary) state-dependent frequency-based HMMs [12]. As shown in [13], a secondary HMM can also be used to extract robust ASR fe ...
Automatic speech recognition (ASR) performance falls dramatically with the level of mismatch between training and test data. The human ability to recognise speech when a large proportion of frequencies are dominated by noise has inspired the "missing data" ...
Automatic speech recognition (ASR) performance falls dramatically with the level of mismatch between training and test data. The human ability to recognise speech when a large proportion of frequencies are dominated by noise has inspired the "missing data" ...
In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...
In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of all this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...
