Abstract
This research project aims to develop Malaysian English Continuous Speech Recognition system by adapting US English acoustic model with Malaysian English speech corpus using Maximum a posteriori reasoning (MAP) and Maximum Likelihood Linear Regression (MLLR). During feature extraction stage, the Mel-Frequency Cepstral Coefficients (MFCC) technique was used. The Hidden Markov Model was used as the back end pattern comparison technique. For the purpose of implementation, the CMU Sphinx toolkit, which includes Pocketsphinx and Sphinxtrain as well as an acoustic model, was used to develop a speech recognition system for Malaysian English. Malaysian English speech sample will be recorded and transcribed to produce the training database required for acoustic model adaptation. The adaptation speech corpus were collected from a number of speakers. The outcome of this research could increase the application of Malaysian English speech recognition in Malaysia due to accent problem. The graphical user interface for Malaysian English Speech Recognition system was created with PyCharm Community Edition and Python 3.9 to make it easier for the individual consumer usage. As a result, speech recognition systems that have gone through the MAP adaptation had the best performance. Its average word error rate achieved was 32.84%. average word recognition rate was 72.52% and average sentence error rate was 78.89%.
Keywords: Speech Recognition, Acoustic Model, MAP, MLLR, Pocketsphinx
Authors
Yoong Kah Chung [1] ; Hong Kai Sze [2]
[1][2] Department of Electrical & Electronic Engineering, Faculty of Engineering, Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia
[1] yoongkc-wg17@student.tarc.edu.my ; [2] hongks@tarc.edu.my
Cite Me
Plain Text:
K.C.Yoong, K.S.Hong, "Development of Malaysian English Large Vocabulary Continuous Speech Recognizer using Acoustic Model Adaptation," International Conference on Digital Transformation and Applications (ICDXA) 2021, 2021, pp. 36-48, doi: https://doi.org/10.56453/icdxa.2021.1003.
BibTex:
@INPROCEEDINGS{ICDXA202101,
author={Yoong, Kah Chung and Hong, Kai Sze},
booktitle={International Conference on Digital Transformation and Applications (ICDXA) 2021},
title={Development of Malaysian English Large Vocabulary Continuous Speech Recognizer using Acoustic Model Adaptation},
year={2021},
volume={},
number={},
pages={36-48},
doi={https://doi.org/10.56453/icdxa.2021.1003}}
