Cost Reduction of Acoustic Modeling for Real-Environment Applications Using Unsupervised and Selective Training

摘要

Development of an ASR application such as a speech-oriented guidance system for a real environment is expensive. Most of the costs are due to human labeling of newly collected speech data to construct the acoustic model for speech recognition. Employment