Deep context: end-to-end contextual speech recognition

Understand

In automatic speech recognition (ASR) what a user says depends on the particular context she is in.

• Typically, this context is represented as a set of word n-grams.
• In this work, we present a novel, all-neural, end-to-end (E2E) ASR sys- tem that utilizes such context.
• Our approach, which we re- fer to as Contextual Listen, Attend and Spell (CLAS) jointly- optimizes the ASR components along with embeddings of the context n-grams.