Developments and directions in speech recognition and understanding, Part 1 [DSP Education]

By Janet M. Baker, Li Deng, James R. Glass, Sanjeev Khudanpur, Chin-Hui Lee, Nelson Morgan, Douglas D. O'Shaughnessy. 2009

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Zidong Wang
2. Yurong Liu
3. Xiaohui Liu
4. Weibo Liu
5. Fuad E. Alsaadi
6. Nianyin Zeng
7. Jinling Liang
8. Huijun Gao

Citations in the corpus

• A survey of deep neural network architectures and their applications (2017, methodology): “For example, Gaussian mixture models (GMMs) have been used to develop speech recognition systems by representing the relationship between the acoustic input and the hidden states of the hidden Markov model (HMM) [7].”
• An Overview of Deep-Structured Learning for Information Processing (2011, background): “For example, human speech production and perception systems are both equipped with clearly layered hierarchical structures in transforming the information from the waveform level to the linguistic level (Baker et al., 2009; Deng, 1999, 2003).”