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Active learning for automatic speech recognition
2002
IIEEE International Conference on Acoustics Speech and Signal Processing
State-of-the-art speech recognition systems are trained using transcribed utterances, preparation of which is labor intensive and time-consuming. In this paper, we describe a new method for reducing the transcription effort for training in automatic speech recognition (ASR). Active learning aims at reducing the number of training examples to be labeled by automatically processing the unlabeled examples, and then selecting the most informative ones with respect to a given cost function for a
doi:10.1109/icassp.2002.1004771
fatcat:sbta75o5qncdjlfoixq2aclrw4