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Xuedong Huang

Semi-Continuous Hidden Markov Models for Speech Recognition
Acoustics, Speech, and Signal Processing, 1995
EFFICIENT CEPSTRAL NORMALIZATION for ROBUST SPEECH RECOGNITION Fu-Hua Liu, Richard M
Subphonetic Modeling for Speech Recognition Mei-Yuh Hwang Xuedong Huang
Challenges in Adopting Speech Recognition
The Computer and the Brain, and the Potential of the Other 95%
Big Data for Speech and Language Processing
Making a World of Difference
An Overview of Modern Speech Recognition
When Artificial Intelligence Can Transcribe Everything
Session 2: Language Modeling
Towards Human Parity in Conversational Speech Recognition
Dynamically Configurable Acoustic Models for Speech Recognition
Less Than Human, More Than Machine: Artificial Intelligence
Home Is Where Cortana Is
Front Matter
Minimizing Speaker Variation Effects for Speaker-Independent Speech Recognition Xuedong Huang
Arxiv:1709.06436V1 [Cs.CL] 19 Sep 2017

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A Prototype Reading Coach That Listens: Summary of Project LISTEN Alex Hauptmann, Jack Mostow, Steven F
Notes for UTM Reading Etc READING ===Reading Lists for the 3 Main Speech Courses
Reddy Transcript Final
Improved Hidden Markov Modeling for Speaker-Independent Continuous
An Overview of the SPHINX-II Speech Recognition System
Speech Understanding in Open Tasks
Introduction to Artificial Intelligence CS 486/686 University of Waterloo Plan for Today
Enabling Natural Computing
ENABLING NATURAL COMPUTING Xuedong Huang Microsoft

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