Deep Context: End-to-end Contextual Speech Recognition

• Published in: 2018 IEEE Spoken Language Technology Workshop (SLT) pp. 418 - 425
• Main Authors: Pundak, Golan, Sainath, Tara N., Prabhavalkar, Rohit, Kannan, Anjuli, Zhao, Ding
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2018
• Subjects: Acoustics; attention; Context modeling; Decoding; embedded speech recognition; LAS; listen attend and spell; sequence-to-sequence models; Speech recognition; Task analysis; Training

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 system that utilizes such context. Our approach, which we refer to a...