Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech Recognition (ASR). Nevertheless, we are still far from achieving high-performance ASR systems. Some alternative approaches, most of them based on Artificial Neural Networks (ANNs), were proposed during the late eighties and early nineties. Some of them tackled the ASR problem using predictive ANNs, while others proposed hybrid HMM/ANN systems. However, despite some achievements, nowadays, the preponderance of Markov Models is a fact. During the last decade, however, a new tool appeared in the field of machine learning that has proved to be able to cope with hard classification problems in several fields of application: the Support Vector Mac...
Neural networks, especially those with more than one hidden layer, have re-emerged in Automatic Spee...
While the temporal dynamics of speech can be represented very efficiently by Hidden Markov Models (H...
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dyn...
Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech ...
Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech ...
Support Vector Machines (SVMs) are state-of-the-art methods for machine learning but share with more...
Using discriminative classifiers, such as Support Vector Machines (SVMs) in combination with, or as ...
Automatic Speech Recognition (ASR) is essentially a problem of pattern classification, however, the...
Although Support Vector Machines (SVMs) have been proved to be very powerful classifiers, they still...
In the last years, support vector machines (SVMs) have shown excellent performance in many applicati...
The improved theoretical properties of Support Vector Machines with respect to other machine learnin...
In spite of the advances accomplished throughout the last decades, automatic speech recognition (ASR...
In spite of the advances accomplished throughout the last decades by a number of research teams, Aut...
Hidden Markov models (HMM) with Gaussian mixture observation densities are the dominant approach in ...
Automatic Speech Recognition (ASR) is a challenging classification task over sequences of acoustic f...
Neural networks, especially those with more than one hidden layer, have re-emerged in Automatic Spee...
While the temporal dynamics of speech can be represented very efficiently by Hidden Markov Models (H...
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dyn...
Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech ...
Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech ...
Support Vector Machines (SVMs) are state-of-the-art methods for machine learning but share with more...
Using discriminative classifiers, such as Support Vector Machines (SVMs) in combination with, or as ...
Automatic Speech Recognition (ASR) is essentially a problem of pattern classification, however, the...
Although Support Vector Machines (SVMs) have been proved to be very powerful classifiers, they still...
In the last years, support vector machines (SVMs) have shown excellent performance in many applicati...
The improved theoretical properties of Support Vector Machines with respect to other machine learnin...
In spite of the advances accomplished throughout the last decades, automatic speech recognition (ASR...
In spite of the advances accomplished throughout the last decades by a number of research teams, Aut...
Hidden Markov models (HMM) with Gaussian mixture observation densities are the dominant approach in ...
Automatic Speech Recognition (ASR) is a challenging classification task over sequences of acoustic f...
Neural networks, especially those with more than one hidden layer, have re-emerged in Automatic Spee...
While the temporal dynamics of speech can be represented very efficiently by Hidden Markov Models (H...
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dyn...