TY - GEN
T1 - Paramount—A Hidden Markov Model Based Intelligent Voice Assistant
AU - Hegde, Manoj Ishwar
AU - Manvitha Shivalingappa, M. P.
AU - Sen, Snigdha
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - Speech is a basic form of communication between human beings. Every human wants to work in an efficient and convenient environment. This voice assistant aids in accomplishing this task. The voice assistant is a software program that has the ability to convert voice input into commands. The main objective of our paper is to convert speech input into text efficiently, which is understandable by the machine. The output is the execution of the command. This is a custom software program that performs general tasks and also some exclusive tasks. It makes a preliminary exploration of the application of speech recognition in various fields. It is an intelligent program that reacts to voice instructions and can be used with any device, which includes desktop/laptop computers, speakers, wearable technology, TV consoles, gaming consoles, tablets, smartphones, virtual reality (VR) headsets, automobiles, and Internet of Things (IoT) gadgets. In our voice assistant, we are using Mel-frequency cestrum coefficient (MFCC) (i.e., feature vector) and vector quantization (VQ-CODE BOOK), hidden Markov model (HMM) (feature matching) to recognize the commands.
AB - Speech is a basic form of communication between human beings. Every human wants to work in an efficient and convenient environment. This voice assistant aids in accomplishing this task. The voice assistant is a software program that has the ability to convert voice input into commands. The main objective of our paper is to convert speech input into text efficiently, which is understandable by the machine. The output is the execution of the command. This is a custom software program that performs general tasks and also some exclusive tasks. It makes a preliminary exploration of the application of speech recognition in various fields. It is an intelligent program that reacts to voice instructions and can be used with any device, which includes desktop/laptop computers, speakers, wearable technology, TV consoles, gaming consoles, tablets, smartphones, virtual reality (VR) headsets, automobiles, and Internet of Things (IoT) gadgets. In our voice assistant, we are using Mel-frequency cestrum coefficient (MFCC) (i.e., feature vector) and vector quantization (VQ-CODE BOOK), hidden Markov model (HMM) (feature matching) to recognize the commands.
UR - https://www.scopus.com/pages/publications/85172233752
UR - https://www.scopus.com/inward/citedby.url?scp=85172233752&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-3878-0_64
DO - 10.1007/978-981-99-3878-0_64
M3 - Conference contribution
AN - SCOPUS:85172233752
SN - 9789819938773
T3 - Lecture Notes in Networks and Systems
SP - 755
EP - 765
BT - Proceedings of International Conference on Data Analytics and Insights, ICDAI 2023
A2 - Chaki, Nabendu
A2 - Roy, Nilanjana Dutta
A2 - Debnath, Papiya
A2 - Saeed, Khalid
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Data Analytics and Insights, ICDAI 2023
Y2 - 11 May 2023 through 13 May 2023
ER -
