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Automatic Speech Recognition - 2009

Offered By: Center for Language & Speech Processing(CLSP), JHU via YouTube

Tags

Machine Learning Courses Signal Processing Courses Hidden Markov Models Courses Feature Extraction Courses

Course Description

Overview

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Explore the fundamentals of automatic speech recognition in this comprehensive lecture delivered by Brian Kingsbury in 2009 at the Center for Language & Speech Processing (CLSP) at Johns Hopkins University. Delve into the core concepts, techniques, and challenges of converting spoken language into written text. Learn about acoustic modeling, language modeling, and decoding algorithms that form the backbone of speech recognition systems. Gain insights into the historical development of ASR technology and its applications in various domains. Discover how machine learning and statistical methods are applied to improve recognition accuracy and robustness. Examine the challenges posed by different accents, background noise, and speaker variability. Understand the evaluation metrics used to assess the performance of speech recognition systems. This 1-hour and 21-minute talk provides a solid foundation for researchers, students, and professionals interested in the field of automatic speech recognition.

Syllabus

Automatic Speech Recognition - Brian Kingsbury - 2009


Taught by

Center for Language & Speech Processing(CLSP), JHU

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