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Language is the most important means of communication and speech is its main medium. Speech is the most direct and natural method of communication between humans and even between human and machine. People who do not have disabilities can converse with each other in natural language, however people who have disabilities, such as Deafness or Dumbness, can only communicate by texting and sign language. Speech detection/recognition is a sub-field of computer science that enable the recognition and translation of spoken language into text by computers. The proposed system tries to implement more by converting audio to text and as well as text to speech which are more useful. For conversion of speech to text we use hidden Markov model(HMM). This project also translates the languages which is helpful for illiterate people too. This translation of language can be done for speech to text using Recurrent Neural Network (RNN).
Keywords:
Speech recognition, Communication, signal processing, Language translation
Cite Article:
"BIDIRECTIONAL LANGUAGE CONVERSION USING RNN ALGORITHM ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1052 - 1057, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304171.pdf
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000205177
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator