Augmented Latent Features of Deep Neural Network-Based Automatic Speech Recognition for Motor-Driven Robots
- Title
- Augmented Latent Features of Deep Neural Network-Based Automatic Speech Recognition for Motor-Driven Robots
- Author
- 장준혁
- Keywords
- automatic speech recognition; human-robot interaction; deep learning; bottleneck layer; latent feature; bottleneck network
- Issue Date
- 2020-07
- Publisher
- MDPI
- Citation
- APPLIED SCIENCES-BASEL, v. 10, no. 13, article no. 4602
- Abstract
- Speech recognition for intelligent robots seems to suffer from performance degradation due to ego-noise. The ego-noise is caused by the motors, fans, and mechanical parts inside the intelligent robots especially when the robot moves or shakes its body. To overcome the problems caused by the ego-noise, we propose a robust speech recognition algorithm that uses motor-state information of the robot as an auxiliary feature. For this, we use two deep neural networks (DNN) in this paper. Firstly, we design the latent features using a bottleneck layer, one of the internal layers having a smaller number of hidden units relative to the other layers, to represent whether the motor is operating or not. The latent features maximizing the representation of the motor-state information are generated by taking the motor data and acoustic features as the input of the first DNN. Secondly, once the motor-state dependent latent features are designed at the first DNN, the second DNN, accounting for acoustic modeling, receives the latent features as the input along with the acoustic features. We evaluated the proposed system on LibriSpeech database. The proposed network enables efficient compression of the acoustic and motor-state information, and the resulting word error rate (WER) are superior to that of a conventional speech recognition system.
- URI
- https://www.mdpi.com/2076-3417/10/13/4602https://repository.hanyang.ac.kr/handle/20.500.11754/169489
- ISSN
- 2076-3417
- DOI
- 10.3390/app10134602
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
- Files in This Item:
- Augmented Latent Features of Deep Neural Network-Based Automatic Speech Recognition for Motor-Driven Robots.pdfDownload
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