VQ-T: RNN Transducers using Vector-Quantized Prediction Network States

VQ-T: RNN Transducers using Vector-Quantized Prediction Network States

3 August 2022

Jiatong Shi

Shinji Watanabe

Brian Kingsbury

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Papers citing "VQ-T: RNN Transducers using Vector-Quantized Prediction Network States"

9 / 9 papers shown

Title
Advancing RNN Transducer Technology for Speech Recognition G. Saon Zoltan Tueske Daniel Bolaños Brian Kingsbury 92 88 0 17 Mar 2021
Less Is More: Improved RNN-T Decoding Using Limited Label Context and Path Merging Rohit Prabhavalkar Yanzhang He David Rybach S. Campbell A. Narayanan Trevor Strohman Tara N. Sainath 106 35 0 12 Dec 2020
Approximating probabilistic models as weighted finite automata A. Suresh Brian Roark Michael Riley Vlad Schogol 67 11 0 21 May 2019
Very Deep Self-Attention Networks for End-to-End Speech Recognition Ngoc-Quan Pham T. Nguyen Jan Niehues Markus Müller Sebastian Stüker A. Waibel 71 161 0 30 Apr 2019
State-of-the-art Speech Recognition With Sequence-to-Sequence Models Chung-Cheng Chiu Tara N. Sainath Yonghui Wu Rohit Prabhavalkar Patrick Nguyen ... Katya Gonina Navdeep Jaitly Yue Liu J. Chorowski M. Bacchiani AI4TS 93 1,154 0 05 Dec 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 363 5,388 0 03 Nov 2016
Listen, Attend and Spell William Chan Navdeep Jaitly Quoc V. Le Oriol Vinyals RALM 163 2,269 0 05 Aug 2015
Attention-Based Models for Speech Recognition J. Chorowski Dzmitry Bahdanau Dmitriy Serdyuk Kyunghyun Cho Yoshua Bengio 129 2,611 0 24 Jun 2015
Sequence Transduction with Recurrent Neural Networks Alex Graves 195 1,872 0 14 Nov 2012

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