Natural language processing enables computer and machines to understand and speak human languages. Speech recognition is a process in which computer understand the human language and processes further instructions as per recognition of the human language. The human language varies so the machine or computer needs entirely different algorithms as the human languages differ in various aspects, such as sounds, phonemes, words, meanings and much more. Understanding human language is a challenging job and for this purpose Hidden Markov Models are used commonly as they possess promising results in understanding human language. A survey of various researches employing Hidden Markov models is presented to highlight the importance of HMM in the proc...
This thesis investigates a stochastic modeling approach to word hypothesis of phonetic strings for a...
During the last decade the field of speech recognition has used the theory of hidden Markov models (...
Hidden Markov Models (HMMs) provides an effective framework for the modeling of time-varying sequenc...
Several feature extraction techniques, algorithms and toolkits are researched to investigate how spe...
The purpose with this final master degree project was to develop a speech recognition tool, to make ...
Abstract. It was a great improvement for the speech signal digital processing technology to use the ...
The speech recognition field is one of the most challenging fields that has faced scientists for a l...
The speech recognition field is one of the most challenging fields that has faced scientists for a l...
This thesis introduces an autoregressive hidden Markov model (HMM) and demonstrates its application ...
Voice control is one of the perspective areas of interdisciplinary field called Human Machine Interf...
Although initially introduced and studied in the late 1960s and early 1970s, statistical methods of ...
In this paper the incorporation of important phonetic properties into hidden Markov models (HMM) is ...
Hidden Markov models (HMMs) are the predominant methodology for automatic speech recognition (ASR) s...
Automatic Speech Recognition (ASR) systems utilize statistical acoustic and language models to find ...
The field of Automatic Speech Recognition (ASR) is about 60 years old. There have been many interest...
This thesis investigates a stochastic modeling approach to word hypothesis of phonetic strings for a...
During the last decade the field of speech recognition has used the theory of hidden Markov models (...
Hidden Markov Models (HMMs) provides an effective framework for the modeling of time-varying sequenc...
Several feature extraction techniques, algorithms and toolkits are researched to investigate how spe...
The purpose with this final master degree project was to develop a speech recognition tool, to make ...
Abstract. It was a great improvement for the speech signal digital processing technology to use the ...
The speech recognition field is one of the most challenging fields that has faced scientists for a l...
The speech recognition field is one of the most challenging fields that has faced scientists for a l...
This thesis introduces an autoregressive hidden Markov model (HMM) and demonstrates its application ...
Voice control is one of the perspective areas of interdisciplinary field called Human Machine Interf...
Although initially introduced and studied in the late 1960s and early 1970s, statistical methods of ...
In this paper the incorporation of important phonetic properties into hidden Markov models (HMM) is ...
Hidden Markov models (HMMs) are the predominant methodology for automatic speech recognition (ASR) s...
Automatic Speech Recognition (ASR) systems utilize statistical acoustic and language models to find ...
The field of Automatic Speech Recognition (ASR) is about 60 years old. There have been many interest...
This thesis investigates a stochastic modeling approach to word hypothesis of phonetic strings for a...
During the last decade the field of speech recognition has used the theory of hidden Markov models (...
Hidden Markov Models (HMMs) provides an effective framework for the modeling of time-varying sequenc...