Grace Hopper India Annual Conference Schedule


Text and Speech Analytics for Dialog Modeling and Word Recognition

December 8 4:15 pm - 5:15 pm
TRACK: Technical - Data Science and Machine Learning
Aura 1
LEVEL: Not applicable

Two trends — the exploding popularity of mobile messaging apps and advances in artificial intelligence — are coinciding to enable a new generation of tools that enable brands to communicate with customers in powerful new ways at reduced cost. Retailers and technology firms are experimenting with chatbots, powered by a combination of machine learning, natural language processing, and live operators, to provide customer service, sales support, and other commerce-related functions. In this presentation we first present the end-to-end design of a VA for chat, from scoping of intents to handling nuances of chat conversations like context-passing and multiple turns in the conversation. Next we focus on speech recognition by specifically examining the problem of how the Hopfield net associative memory framework can be adapted for speech recognition. We present early results on these issues and show the basic feasibility and merits of the Hopfield network formulation for speech recognition