Efficient Sequence Training of Attention Models using Approximative Recombination

18 October 2021

Papers citing "Efficient Sequence Training of Attention Models using Approximative Recombination"

8 / 8 papers shown

Title
Investigating Methods to Improve Language Model Integration for Attention-based Encoder-Decoder ASR Models Mohammad Zeineldeen Aleksandr Glushko Wilfried Michel Albert Zeyer Ralf Schluter Hermann Ney AuLLM 34 39 0 12 Apr 2021
On Minimum Word Error Rate Training of the Hybrid Autoregressive Transducer Liang Lu Zhong Meng Naoyuki Kanda Jinyu Li Jiawei Liu 47 12 0 23 Oct 2020
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations Alexei Baevski Henry Zhou Abdel-rahman Mohamed Michael Auli SSL 179 5,734 0 20 Jun 2020
Early Stage LM Integration Using Local and Global Log-Linear Combination Wilfried Michel Ralf Schluter Hermann Ney 29 11 0 20 May 2020
Minimum Bayes Risk Training of RNN-Transducer for End-to-End Speech Recognition Chao Weng Chengzhu Yu Jia Cui Chunlei Zhang Dong Yu 105 39 0 28 Nov 2019
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition Daniel S. Park William Chan Yu Zhang Chung-Cheng Chiu Barret Zoph E. D. Cubuk Quoc V. Le VLM 149 3,435 0 18 Apr 2019
Minimum Word Error Rate Training for Attention-based Sequence-to-Sequence Models Rohit Prabhavalkar Tara N. Sainath Yonghui Wu Patrick Nguyen Zhiwen Chen Chung-Cheng Chiu Anjuli Kannan 40 161 0 05 Dec 2017
On Using Monolingual Corpora in Neural Machine Translation Çağlar Gülçehre Orhan Firat Kelvin Xu Kyunghyun Cho Loïc Barrault Huei-Chi Lin Fethi Bougares Holger Schwenk Yoshua Bengio 96 559 0 11 Mar 2015