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A review of on-device fully neural end-to-end automatic speech
  recognition algorithms
v1v2v3 (latest)

A review of on-device fully neural end-to-end automatic speech recognition algorithms

Asilomar Conference on Signals, Systems and Computers (Asilomar), 2020
14 December 2020
Chanwoo Kim
Dhananjaya N. Gowda
Dongsoo Lee
Jiyeon Kim
Ankur Kumar
Sungsoo Kim
Abhinav Garg
C. Han
ArXiv (abs)PDFHTML

Papers citing "A review of on-device fully neural end-to-end automatic speech recognition algorithms"

9 / 9 papers shown
Macro-block dropout for improved regularization in training end-to-end
  speech recognition models
Macro-block dropout for improved regularization in training end-to-end speech recognition modelsSpoken Language Technology Workshop (SLT), 2022
Chanwoo Kim
Sathish Indurti
Jinhwan Park
Wonyong Sung
150
0
0
29 Dec 2022
PENTATRON: PErsonalized coNText-Aware Transformer for Retrieval-based
  cOnversational uNderstanding
PENTATRON: PErsonalized coNText-Aware Transformer for Retrieval-based cOnversational uNderstandingConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Niranjan Uma Naresh
Ziyan Jiang
Ankit
Sungjin Lee
Jie Hao
Xing Fan
Chenlei Guo
232
7
0
22 Oct 2022
Towards Personalization of CTC Speech Recognition Models with Contextual
  Adapters and Adaptive Boosting
Towards Personalization of CTC Speech Recognition Models with Contextual Adapters and Adaptive Boosting
Saket Dingliwal
Monica Sunkara
S. Bodapati
S. Ronanki
Jeffrey J. Farris
Katrin Kirchhoff
310
0
0
18 Oct 2022
Two-Pass End-to-End ASR Model Compression
Two-Pass End-to-End ASR Model CompressionAutomatic Speech Recognition & Understanding (ASRU), 2021
Nauman Dawalatabad
Tushar Vatsal
Ashutosh Gupta
Sungsoo Kim
Shatrughan Singh
Dhananjaya N. Gowda
Chanwoo Kim
139
6
0
08 Jan 2022
Semi-supervised transfer learning for language expansion of end-to-end
  speech recognition models to low-resource languages
Semi-supervised transfer learning for language expansion of end-to-end speech recognition models to low-resource languagesAutomatic Speech Recognition & Understanding (ASRU), 2021
Jiyeon Kim
Mehul Kumar
Dhananjaya N. Gowda
Abhinav Garg
Chanwoo Kim
137
9
0
19 Nov 2021
A comparison of streaming models and data augmentation methods for
  robust speech recognition
A comparison of streaming models and data augmentation methods for robust speech recognitionAutomatic Speech Recognition & Understanding (ASRU), 2021
Jiyeon Kim
Mehul Kumar
Dhananjaya N. Gowda
Abhinav Garg
Chanwoo Kim
159
6
0
19 Nov 2021
Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming
  E2E ASR via Supernet
Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet
Haichuan Yang
Yuan Shangguan
Dilin Wang
Meng Li
P. Chuang
Xiaohui Zhang
Ganesh Venkatesh
Ozlem Kalinli
Vikas Chandra
236
14
0
15 Oct 2021
Noisy Training Improves E2E ASR for the Edge
Noisy Training Improves E2E ASR for the Edge
Dilin Wang
Yuan Shangguan
Haichuan Yang
P. Chuang
Jiatong Zhou
Meng Li
Ganesh Venkatesh
Ozlem Kalinli
Vikas Chandra
270
4
0
09 Jul 2021
StableEmit: Selection Probability Discount for Reducing Emission Latency
  of Streaming Monotonic Attention ASR
StableEmit: Selection Probability Discount for Reducing Emission Latency of Streaming Monotonic Attention ASR
Hirofumi Inaguma
Tatsuya Kawahara
217
4
0
01 Jul 2021
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