Building An Automatic Speech Recognition System for Home Automation

Authors

  • Mohamed Aboulkhir Spatial Remote Sensing -Signal Processing Applied Maths &Computer Science Decision Support Laboratory, Abdelmalek Essaadi University, National School of Applied Sciences, 93000,Tetouan,Morocco.
  • Samira Khoulji Spatial Remote Sensing -Signal Processing Applied Maths &Computer Science Decision Support Laboratory, Abdelmalek Essaadi University, National School of Applied Sciences, 93000,Tetouan,Morocco.
  • Reda Jourani Polydisciplinary Faculty of Tetouan, Abdelmalek Essaadi University, Tetouan, Morocco.
  • ML Kerkeb Spatial Remote Sensing -Signal Processing Applied Maths &Computer Science Decision Support Laboratory, Abdelmalek Essaadi University, National School of Applied Sciences, 93000,Tetouan,Morocco.

DOI:

https://doi.org/10.14738/tmlai.54.3190

Keywords:

Speech recognition, acoustic model, language model, HMM, n-gram, domotics, Kaldi.

Abstract

This paper presents a study on automatic speech recognition (ASR) systems applied to home automation. So a detailed study of the architecture of speech recognition systems was carried out. The objective is to select a speech recognition software that must operate in remote speech conditions and in a noisy environment. The proposed system is using an ASR toolkit called Kaldi, which must communicate as an open platform communication (OPC) client developed in C++, with any home automation system. The latter behaves like an OPC server.

 

References

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Published

2017-09-01

How to Cite

Aboulkhir, M., Khoulji, S., Jourani, R., & Kerkeb, M. (2017). Building An Automatic Speech Recognition System for Home Automation. Transactions on Engineering and Computing Sciences, 5(4). https://doi.org/10.14738/tmlai.54.3190

Issue

Section

Special Issue : 1st International Conference on Affective computing, Machine Learning and Intelligent Systems

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