Lecture 12: End-to-End Models for Speech Processing
Lecture 12 looks at traditional speech recognition systems and motivation for end-to-end models. Also covered are Connectionist Temporal Classification (CTC) and Listen Attend and Spell (LAS), a sequence-to-sequence based model for speech recognition.
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Natural Language Processing with Deep Learning
Instructors:
- Chris Manning
- Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.
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http://stanfordonline.stanford.edu/