Topic
Devanagari
About: Devanagari is a research topic. Over the lifetime, 655 publications have been published within this topic receiving 7428 citations. The topic is also known as: Deva nagari & Hindi Script.
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TL;DR: The discrimination of the similar characters, which is one of the major sources of classification error is discussed, and the Fisher linear discriminant model is suggested to detect the critical region, which will be used to extract the additional features in order to minimize the classification errors in the end results.
Abstract: The research works in Handwritten Devanagari Characters are continually evolving into new challenges, which exposed the new sources of further research work like, character normalization, gray-leve...
3 citations
01 Oct 2016
TL;DR: This paper presents few techniques for optimizing the recognition accuracy at pre-classification stage, feature extraction stage and recognition stage of Devanagari script.
Abstract: Devanagari script has character set with rich structural features that makes the recognition of unconstrained handwritten Devanagari characters difficult However, these features can be used to divide the characters into different categories. This paper presents few techniques for optimizing the recognition accuracy at pre-classification stage, feature extraction stage and recognition stage. Initially, the pre-classification of the characters is done into different classes using various structural features. Then features are extracted using optimized feature extraction techniques. Finally, the recognition is done using neural network. In this paper, different neural networks are implemented and their performances are analyzed.
3 citations
Book•
13 Jan 2009
TL;DR: The 1810 dictionary of Marathi as mentioned in this paper provides a detailed description of the Devanagari alphabet, its word and sentence formation, and its complex tense, voice, gender, agreement, inflection, and case systems.
Abstract: Marathi, an official language of Maharashtra and Goa, is among the twenty most widely spoken languages in the world. The southernmost Indo-Aryan language, it is also spoken in Gujarat, Madhya Pradesh, Karnataka, and Daman and Diu, and is believed to be over 1,300 years old, with its origins in Sanskrit. First published in 1805, this grammar of Marathi (then known as Mahratta) was compiled by the Baptist missionary William Carey (1761–1834) during his time in India. Its purpose was to assist Carey's European students at Fort William College in their learning of the language, and it is comprehensive in ITS coverage, providing numerous examples. Containing detailed descriptions of Marathi's Devanagari alphabet, its word and sentence formation, and its complex tense, voice, gender, agreement, inflection, and case systems, the work remains an invaluable resource for linguists today. Carey's 1810 dictionary of Marathi is also reissued in this series.
3 citations
01 Jan 2017
TL;DR: This paper investigates the use of some candidate speech synthesizers inclusive of Indian and non-Indian languages in the context of high quality TTS Systems using syllable as the unit for synthesis.
Abstract: Text to Speech (TTS) Synthesizer is an application that converts text to speech. A TTS has applications that make computer systems interactive and help its users especially the visually challenged. Concatenative synthesis technique uses different units of speech such as words, syllables, diaphones and phonemes. Most of the Indian languages are syllabic in nature and thus syllables are best suited as the unit of synthesis over phonemes and diphones. Syllabification is used in Speech Synthesis Systems in producing natural sounding speech and in speech recognizers in detecting words. This paper investigates the use of some candidate speech synthesizers inclusive of Indian and non-Indian languages in the context of high quality TTS Systems using syllable as the unit for synthesis. Analysis indicates that the syllable based approach performs better for Indian languages. Forward and backward approach to generate syllables is implemented for Indian languages written in Devanagari Script like Hindi, Marathi and Konkani for the development of a TTS system. The system is developed for different units of speech such as words, syllables, diphones and phonemes. The test results indicate positive results in terms of naturalness for Konkani language taking into account the implementation of the Konkani phonological rules. Each language has specific phonological rules requiring attention for the development of a TTS system with high naturalness and intelligibility rather than only using syllable as the unit for synthesis. Thus it becomes complex to develop a common generic TTS system for different languages.
3 citations
TL;DR: An attempt is made to address the most important results reported so far and it is also tried to highlight the beneficial directions of the research till date.
Abstract: In India, many people use Devanagari script for documentation. There has been a significant improvement in the research related to the recognition of printed as well as handwritten Devanagari text in the past few years. Basically Character recognition techniques associate a symbolic identity with the image of a character. Since creating an algorithm with a one hundred percent correct recognition rate is quite probably impossible in our world of noise and different font styles, it is important to design character recognition algorithms with these failures in mind so that when mistakes are inevitably made, they will at least be understandable and predictable to the person working with the program. An attempt is made to address the most important results reported so far and it is also tried to highlight the beneficial directions of the research till date.
3 citations