Improved Hidden Markov Modeling for Speaker-Independent Continuous Speech Recognition

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Improved lexicon modeling for continuous speech recognition

We propose the stochastic lexicon model which represents the pronunciation variations to optimally cope with the continuous speech recognizer. In this lexicon model, the baseform of words are represented by subword states and probability distribution of subwords as hidden Markov model. Also, proposed approach can be applied to system employing non-linguistic recognition units and lexicon is aut...

شبکه عصبی پیچشی با پنجره‌های قابل تطبیق برای بازشناسی گفتار

Although, speech recognition systems are widely used and their accuracies are continuously increased, there is a considerable performance gap between their accuracies and human recognition ability. This is partially due to high speaker variations in speech signal. Deep neural networks are among the best tools for acoustic modeling. Recently, using hybrid deep neural network and hidden Markov mo...

Recognition of Speech with Non-random Attributes

Most of current speech recognition systems are based on Hidden Markov Models assuming that speech features are sequence of stationary stochastic processes. However, there are certain speech attributes, such as background noise type or speaker voice color, that do not have stochastic character. This fact is often ignored, by designers of robust speaker independent recognition system. In this wor...