More Expressive Architectures Make a Big Difference
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Babel resources
Description:
Explore multilingual speech representations for low-resource speech processing in this 40-minute talk by Brian Kingsbury from IBM. Discover how to achieve good automatic speech recognition performance with limited data for thousands of languages worldwide. Learn about the IARPA Babel Program, keyword search techniques, and various neural network architectures including Deep Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. Understand the challenges and solutions for processing languages with limited resources, and gain insights into the importance of multilingual features in reducing the amount of data needed for training speech recognition systems in new languages. Examine three use cases and learn how more expressive architectures significantly impact performance. Ideal for researchers and professionals interested in advancing speech processing technologies for low-resource languages.
Multilingual Representations for Low-Resource Speech Processing