Abstract
In this paper, we propose a speech recognition method based on CLSTM-HMM hybrid acoustic model for home service robots that cannot recognize speech commands effectively in domestic noise. Hybrid speech features characterize dynamic and static features, which can characterize speech features well, CNN has advantages in selecting good features, LSTM and HMM are usually used for speech recognition, which both methods have demonstrated strong capabilities. The experimental results prove that the recognition rate of home service robots based on CLSTM-HMM speech recognition method can reach 91.44%, 91.36% and 90.92%, respectively. Over all, the home service robots based on CLSTM-HMM speech recognition method have ideal recognition performance in domestic noise.
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Acknowledgements
This work was supported by Natural Science Foundation of China [51905405]; Key research & Development plan of Shaanxi province China [2019ZDLGY01-08]; Ministr of Education Engineering Science and Technology Talent Training Research Project of China [18JDGC029].
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Zhao, C., Wang, X., Zhang, L. (2021). Speech Recognition Method for Home Service Robots Based on CLSTM-HMM Hybrid Acoustic Model. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Bevilacqua, V. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12836. Springer, Cham. https://doi.org/10.1007/978-3-030-84522-3_20
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DOI: https://doi.org/10.1007/978-3-030-84522-3_20
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