This paper describes, and evaluates on a large scale, the lattice based framework for discriminative training of large vocabulary speech recognition systems based on Gaussian mixture hidden Markov models (HMMs). This paper concentrates on the maximum mutual information estimation (MMIE) criterion wh
Training data selection for improving discriminative training of acoustic models
โ Scribed by Berlin Chen; Shih-Hung Liu; Fang-Hui Chu
- Publisher
- Elsevier Science
- Year
- 2009
- Tongue
- English
- Weight
- 647 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0167-8655
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
One unique feature of neural networks is that they have to be trained to function. In developing an iterative neural network technique for model updating of structures, it has been shown that the number of training samples required increases exponentially as the number of parameters to be updated in
Oral practice examinations (OPEs) are used in many anaesthesiology programmes to familiarize anaesthesiology residents with the format of the oral examination administered by the American Board of Anesthesiology. The OPE outcome ("nal grade) consists of &De"nite Not Pass', &Probable Not Pass', &Prob