Optical Character Recognition (OCR) is a very old and of great interest in pattern recognition field. The recognition of cursive scripts like Persian and Arabic languages is a difficult task as their segmentation suffers from serious problems in different languages. Segmentation is a process of dividing cursive words into smaller parts in order to decrease complexity and increase accuracy of re...

A new scheme to represent phonological changes during continuous speech recognition is suggested. A phonological tag coupled with its morphological tag is designed to represent the conditions of Korean phonological changes. A pairwise language model of these morphological and phonological tags is implemented in Korean speech recognition system. Performance of the model is verified through the T...

Phonemes are the standard modelling unit in HMM-based continuous speech recognition systems. Visemes are the equivalent unit in the visual domain, but there is less agreement on precisely what visemes are, or how many to model on the visual side in audio-visual speech recognition systems. This paper compares the use of 5 viseme maps in a continuous speech recognition task. The focus of the stud...

We present a large vocabulary, continuous speech recognition system based on Linked Predictive Neural Networks (LPNN's). The system uses neural networks as predictors of speech frames, yielding distortion measures which are used by the One Stage DTW algorithm to perform continuous speech recognition. The system, already deployed in a Speech to Speech Translation system, currently achieves 95%, ...

Segmentation of speech into its corresponding phones has become very important issue in many speech processing areas such as speech recognition, speech analysis, speech synthesis, and speech database. In this paper, for accurate segmentation in speech recognition applications, we introduce Distinctive Phonetic Feature (DPF) based feature extraction using a twostage NN (Neural Networks) system c...

A speech recognition system implements the task of automatically transcribing speech into text. As computer power has advanced and sophisticated tools have become available, there has been significant progress in this field. But a huge gap still exists between the performance of the Automatic Speech Recognition (ASR) systems and human listeners. In this thesis, a novel signal analysis technique...

In recent research, we have demonstrated that linguistic features can be used to improve speech recognition for an isolated vocabulary recognition task. This paper addresses two important new research problems in our attempts to build a two-stage speech recognition system using linguistic features. First, through a controlled study we show that our knowledge-driven feature sets perform competit...