A deep recurrent approach for acoustic-to-articulatory inversion

@article{Liu2015ADR,
  title={A deep recurrent approach for acoustic-to-articulatory inversion},
  author={Peng Liu and Quanjie Yu and Zhiyong Wu and Shiyin Kang and Helen M. Meng and Lianhong Cai},
  journal={2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2015},
  pages={4450-4454}
}
To solve the acoustic-to-articulatory inversion problem, this paper proposes a deep bidirectional long short term memory recurrent neural network and a deep recurrent mixture density network. The articulatory parameters of the current frame may have correlations with the acoustic features many frames before or after. The traditional pre-designed fixed-length context window may be either insufficient or redundant to cover such correlation information. The advantage of recurrent neural network is… CONTINUE READING

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