Performance Analysis and Recognition of Speech using Recurrent Neural Network

  • Bishon Lamichanne Paschimanchal Campus, Institute of Engineering, Tribhuvan University, Nepal
  • Hari K.C. Paschimanchal Campus, Institute of Engineering, Tribhuvan University, Nepal
Keywords: Recurrent Neural Network, speech recognition, spoken words, Artificial Intelligence, Machine, multi-layer perception

Abstract

Speech is one of the most natural ways to communicate between people. It plays an important role in our daily lives. To make machines able to talk with people is a challenging but very useful task. A crucial step is to enable machines to recognize and understand what people are saying. Hence, speech recognition becomes a key technique providing an interface for communication between machines and humans. There has been a long research history on speech recognition. Neural network is known as a technique that has ability to classify nonlinear problem. Today, lots of research are going in the field of speech recognition with the help of the Neural Network. Even though positive results have been obtained from continuous study, research on minimizing the error rate is still gaining lots attention. The English language offers a number of challenges for speech recognition. This paper implements the RNN to analyze and recognize speech from the set of spoken words.

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Author Biographies

Bishon Lamichanne, Paschimanchal Campus, Institute of Engineering, Tribhuvan University, Nepal

Department of Electronics and Computer Engineering

Hari K.C., Paschimanchal Campus, Institute of Engineering, Tribhuvan University, Nepal

Department of Electronics and Computer Engineering

Published
2019-07-01
How to Cite
Lamichanne, B., & K.C., H. (2019). Performance Analysis and Recognition of Speech using Recurrent Neural Network. Technical Journal, 1(1), 87-95. https://doi.org/10.3126/tj.v1i1.27596
Section
Articles