Recent advances in deep learning for speech research at Microsoft

@article{Deng2013RecentAI,
  title={Recent advances in deep learning for speech research at Microsoft},
  author={L. Deng and J. Li and Jui-Ting Huang and K. Yao and Dong Yu and F. Seide and Michael L. Seltzer and G. Zweig and X. He and J. Williams and Y. Gong and A. Acero},
  journal={2013 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2013},
  pages={8604-8608}
}
  • L. Deng, J. Li, +9 authors A. Acero
  • Published 2013
  • Computer Science
  • 2013 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Deep learning is becoming a mainstream technology for speech recognition at industrial scale. [...] Key Result Potential improvement of these techniques and future research directions are discussed.Expand Abstract
    579 Citations
    Deep learning in acoustic modeling for Automatic Speech Recognition and Understanding - an overview -
    • I. Gavat, D. Militaru
    • Computer Science
    • 2015 International Conference on Speech Technology and Human-Computer Dialogue (SpeD)
    • 2015
    • 10
    From Speech Recognition to Language and Multimodal Processing
    • 30
    • PDF
    Speech Recognition Using Deep Neural Networks: A Systematic Review
    • 104
    Deep learning of split temporal context for automatic speech recognition
    • 5
    • PDF
    Ensemble deep learning for speech recognition
    • 139
    • PDF
    A Survey of Deep Learning Techniques in Speech Recognition
    • 6
    Speech Recognition Using Deep Learning Algorithms
    • 10
    • PDF
    New types of deep neural network learning for speech recognition and related applications: an overview
    • 670
    • PDF
    Speech recognition using deep neural network - recent trends
    • 1
    • Highly Influenced
    • PDF

    References

    SHOWING 1-10 OF 68 REFERENCES
    Investigation of full-sequence training of deep belief networks for speech recognition
    • 208
    • PDF
    Machine Learning Paradigms for Speech Recognition: An Overview
    • Li Deng, X. Li
    • Computer Science
    • IEEE Transactions on Audio, Speech, and Language Processing
    • 2013
    • 232
    • PDF
    Towards deeper understanding: Deep convex networks for semantic utterance classification
    • 95
    • PDF
    An investigation of deep neural networks for noise robust speech recognition
    • 550
    • PDF
    Use of kernel deep convex networks and end-to-end learning for spoken language understanding
    • 92
    • PDF
    Deep Neural Networks for Acoustic Modeling in Speech Recognition
    • 1,999
    • PDF
    Multilingual acoustic models using distributed deep neural networks
    • 258
    • PDF
    Roles of Pre-Training and Fine-Tuning in Context-Dependent DBN-HMMs for Real-World Speech Recognition
    • 192
    • PDF
    Adaptation of context-dependent deep neural networks for automatic speech recognition
    • 201
    • PDF