Isolated Word Speech Recognition Using Mixed Transform

Isolated Word Recognition Using Neural Network for Disordered Speech

The society is fully aware of the needs of impaired people. One such impairment resulting due to articulatory or congenital conditions in human speech production mechanism produces a disordered speech. This disordered speech is difficult to interpret and leads to miscommunication. Thus, the speech enabled helping aid is a good alternative to existing devices designed to assist the impaired spea...

Isolated-word speech recognition using hidden Markov models

Isolated Word Speech Recognition System Using Deep Neural Networks

Speech recognition is the process of converting speech signals into words. For acoustic modeling HMM-GMM is used for many years. For GMM, it requires assumptions near the data distribution for calculating probabilities. For removing this limitation, GMM is replaced by DNN in acoustic model. Deep neural networks are the feed forward neural networks having more than one or multiple layers of hidd...

Development of Isolated Word Speech Recognition System

The isolated word speech recognition system based on dynamic time warping (DTW) has been developed. Speaker adaptation is performed using speaker recognition techniques. Vector quantization is used to create reference templates for speaker recognition. Linear predictive coding (LPC) parameters are used as features for recognition. Performance is evaluated using 12 words of Lithuanian language p...

Fuzzy Clustering Approach Using Data Fusion Theory and its Application To Automatic Isolated Word Recognition

 In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the...