Topics
Hidden Markov ModelPerson
This paper describes a neural-net based isolated word recogniser that has a better performance on a standard multi-speaker database than our reference Hidden Markov Model recogniser. The complete neural net recogniser is formed from two parts: a front-end which transforms the complex acoustic specification of the speech into a simplified phonetic feature specification, and a whole-word discriminator net. Each level was trained separately, thus considerably reducing the time necessary to train the overall system
Speech is an easiest way to communicate with each other. Digital processing of speechsignals is very...
The work presented in this thesis concerns the recognition of isolated words using a pattern matchin...
The work presented in this thesis concerns the recognition of isolated words using a pattern matchin...
Speech recognition is important for successful development of speech recognizers in most real world ...
This paper describes an isolated word recognition method based on distinctive phonetic features (DPF...
This paper argues that neural networks are good vehicles for automatic speech recognition not simply...
This paper investigates the use of feed-forward multi-layer perceptrons trained by back-propagation ...
Abstract. This paper argues that neural networks are good vehicles for automatic speech recognition ...
This paper investigates the use of feed-forward multi-layer perceptrons trained by back-propagation ...
Abstract- Neural network architecture is widely used in computer science for solving complex problem...
In spite of the advances accomplished throughout the last few decades, automatic speech recognition...
The field of digital speech processing may be divided into three distinct and somewhat in- depend...
A set of recurrent artificial neural networks are used for speech recognition. By representing speec...
In this work we do a comparative evaluation between Artificial Neural Networks (RNA's) and Continuou...
The recognition rate of syllables in continuous speech is hampered due t o the large size of t he sy...
Speech is an easiest way to communicate with each other. Digital processing of speechsignals is very...
The work presented in this thesis concerns the recognition of isolated words using a pattern matchin...
The work presented in this thesis concerns the recognition of isolated words using a pattern matchin...
Speech recognition is important for successful development of speech recognizers in most real world ...
This paper describes an isolated word recognition method based on distinctive phonetic features (DPF...
This paper argues that neural networks are good vehicles for automatic speech recognition not simply...
This paper investigates the use of feed-forward multi-layer perceptrons trained by back-propagation ...
Abstract. This paper argues that neural networks are good vehicles for automatic speech recognition ...
This paper investigates the use of feed-forward multi-layer perceptrons trained by back-propagation ...
Abstract- Neural network architecture is widely used in computer science for solving complex problem...
In spite of the advances accomplished throughout the last few decades, automatic speech recognition...
The field of digital speech processing may be divided into three distinct and somewhat in- depend...
A set of recurrent artificial neural networks are used for speech recognition. By representing speec...
In this work we do a comparative evaluation between Artificial Neural Networks (RNA's) and Continuou...
The recognition rate of syllables in continuous speech is hampered due t o the large size of t he sy...
Speech is an easiest way to communicate with each other. Digital processing of speechsignals is very...
The work presented in this thesis concerns the recognition of isolated words using a pattern matchin...
The work presented in this thesis concerns the recognition of isolated words using a pattern matchin...
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