Parts-based models and local features for automatic speech recognition

[摘要] (cont.) We demonstrate the proposed models on various isolated recognition tasks and show the benefits over baseline systems, particularly in noisy conditions and when only limited training data is available. We discuss efficient implementation of the models and describe how they can be combined to build larger recognition systems. It is argued that the flexible templates used in parts-based modeling may provide a better generative model of speech than typical HMMs.

[发布机构] Massachusetts Institute of Technology