A Practitioner’s Look at Speech -to-Text

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Mark Dickison, Technical and Modeling Lead for Capital One’s internal speech recognition team – SpeakEasy

Abstract:

This talk covers the basics of Speech-to-Text using Hidden Markov Models and Gaussian Mixture Models (HMM-GMM). Included will be a discussion of the basics of signal processing for speech recognition, acoustic and language models, and how they are jointly maximized to produce text.

​ As time and interest allows, Neural Networks, and how they can be used either in hybrid with HMM-GMM models will also be covered.

Bio:

Mark Dickison started his career as a computational physicist specializing in network science – acquiring his Ph.D. from Boston University. This was followed by a post-doctoral fellowship at Pennsylvania State in their USP program, which supports the US Defense Threat Reduction Agency. Leaving academia, he joined Booz Allen Hamilton as a data scientist, working with a variety of clients across health, finance, and energy. Mark is currently the Technical and Modeling Lead for Capital One’s internal speech recognition team – SpeakEasy.

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