April 2024
Intermediate to advanced
496 pages
13h 10m
English
book
Automatic Speech Recognition and Translation for Low Resource Languages
by L. Ashok Kumar, D. Karthika Renuka, Bharathi Raja Chakravarthi, Thomas Mandl
Content preview from Automatic Speech Recognition and Translation for Low Resource Languages
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16Deep Neural Machine Translation (DNMT): Hybrid Deep Learning Architecture-Based English-to-Indian Language Translation
Nivaashini M.1*, Priyanka G.2 and Aarthi S.2
1Department of Artificial Intelligence & Data Science, Sri Eshwar College of Engineering, Coimbatore, India
2Department of Computer Science & Engineering, Sri Ramakrishna Engineering College, Coimbatore, India
Abstract
Most Indian dialects need more equal information to prepare machine interpretation (MT). The investigation of machine interpretation has been in progress for a really long time. Machine learning employs artificial intelligence (AI) to automatically translate text between languages without the assistance of human linguists. The disposal of the language hindrance is the essential objective of machine interpretation. Early examinations in this space started by straightforwardly subbing objective language for source language in exactly the same words. In the end, information-driven models like factual, AI, and profound brain machine interpretation strategies turned out to be more common as PC and correspondence innovation progressed. As a direct result of recent advancements in deep learning and AI, particularly in the field of multilingual voice recognition, applications for spoken language translation are playing an increasingly significant role in our day-to-day lives. For deep neural machine translation (DNMT) from English to Hindi, Tamil, Telugu, Malayalam, and Kannada, we create hybrid deep learning ...
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