Construction of Large Scale Isolated Word Speech Corpus in Bangla

A new speech corpus of isolated words in Bangla language has been recorded including high frequent words from a text corpus BdNC01 It has been specifically designed for various research activities related to speaker-independent Bangla speech recognition The database consists of speech of 100 speakers each of them speaking 1081 words Another 50 new speakers were employed to speak all the list of speech to construct a test database Every utterance was repeated 5 times in different days to avoid time variation of speaker property The total 400 hours of recording makes the corpora largest in its type size and language domain This paper describes the motivation for the corpora and the processes undertaken in its construction The paper concludes with the usability of the corpu

Character Recognition

Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field

Continuous speech segmentation using local adaptive thresholding technique in the blocking block area method

Continuous speech is a form of natural human speech that is continuous without a clear boundary between words. In continuous speech recognition, a segmentation process is needed to cut the sentence at the boundary of each word. Segmentation becomes an important step because a speech can be recognized from the word segments produced by this process. The segmentation process in this study was carried out using local adaptive thresholding technique in the blocking block area method. This study aims to conduct performance comparisons for five local adaptive thresholding methods (Niblack, Sauvola, Bradley, Guanglei Xiong and Bernsen) in continuous speech segmentation to obtain the best method and optimum parameter values. Based on the results of the study, Niblack method is concluded as the best method for continuous speech segmentation in Indonesian language with the accuracy value of 95%, and the optimum parameter values for such method are window = 75 and k = 0.2