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Towards a Competitive End-to-End Speech Recognition for CHiME-6 Dinner
  Party Transcription
v1v2v3 (latest)

Towards a Competitive End-to-End Speech Recognition for CHiME-6 Dinner Party Transcription

22 April 2020
A. Andrusenko
A. Laptev
Ivan Medennikov
ArXiv (abs)PDFHTML

Papers citing "Towards a Competitive End-to-End Speech Recognition for CHiME-6 Dinner Party Transcription"

12 / 12 papers shown
Back Transcription as a Method for Evaluating Robustness of Natural
  Language Understanding Models to Speech Recognition Errors
Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition ErrorsConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Marek Kubis
Pawel Skórzewski
Marcin Sowañski
Tomasz Ziętkiewicz
324
9
0
25 Oct 2023
Anchored Speech Recognition with Neural Transducers
Anchored Speech Recognition with Neural TransducersIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Desh Raj
Junteng Jia
Jay Mahadeokar
Chunyang Wu
Niko Moritz
Xiaohui Zhang
Ozlem Kalinli
309
2
0
20 Oct 2022
Direction-Aware Joint Adaptation of Neural Speech Enhancement and
  Recognition in Real Multiparty Conversational Environments
Direction-Aware Joint Adaptation of Neural Speech Enhancement and Recognition in Real Multiparty Conversational EnvironmentsInterspeech (Interspeech), 2022
Yicheng Du
Aditya Arie Nugraha
Kouhei Sekiguchi
Yoshiaki Bando
Mathieu Fontaine
Kazuyoshi Yoshii
148
0
0
15 Jul 2022
Recent Advances in End-to-End Automatic Speech Recognition
Recent Advances in End-to-End Automatic Speech RecognitionAPSIPA Transactions on Signal and Information Processing (TASIP), 2021
Jinyu Li
VLM
549
444
0
02 Nov 2021
Data Augmentation Methods for End-to-end Speech Recognition on
  Distant-Talk Scenarios
Data Augmentation Methods for End-to-end Speech Recognition on Distant-Talk ScenariosInterspeech (Interspeech), 2021
E. Tsunoo
Kentarou Shibata
Chaitanya Narisetty
Yosuke Kashiwagi
Shinji Watanabe
174
13
0
07 Jun 2021
SpeechStew: Simply Mix All Available Speech Recognition Data to Train
  One Large Neural Network
SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network
William Chan
Daniel S. Park
Chris A. Lee
Yu Zhang
Quoc V. Le
Mohammad Norouzi
AI4TS
479
149
0
05 Apr 2021
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource
  End-to-End Speech Recognition
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech RecognitionItalian National Conference on Sensors (INS), 2021
A. Laptev
A. Andrusenko
Ivan Podluzhny
Anton Mitrofanov
Ivan Medennikov
Yuri N. Matveev
VLM
177
15
0
12 Mar 2021
The 2020 ESPnet update: new features, broadened applications,
  performance improvements, and future plans
The 2020 ESPnet update: new features, broadened applications, performance improvements, and future plans
Shinji Watanabe
Florian Boyer
Xuankai Chang
Pengcheng Guo
Tomoki Hayashi
...
Shigeki Karita
Chenda Li
Jing Shi
Aswin Shanmugam Subramanian
Wangyou Zhang
VLM
251
39
0
23 Dec 2020
VenoMave: Targeted Poisoning Against Speech Recognition
VenoMave: Targeted Poisoning Against Speech Recognition
H. Aghakhani
Lea Schonherr
Thorsten Eisenhofer
D. Kolossa
Thorsten Holz
Christopher Kruegel
Giovanni Vigna
AAML
349
20
0
21 Oct 2020
Exploration of End-to-End ASR for OpenSTT -- Russian Open Speech-to-Text
  Dataset
Exploration of End-to-End ASR for OpenSTT -- Russian Open Speech-to-Text Dataset
A. Andrusenko
A. Laptev
Ivan Medennikov
VLM
343
13
0
15 Jun 2020
A New Training Pipeline for an Improved Neural Transducer
A New Training Pipeline for an Improved Neural Transducer
Albert Zeyer
André Merboldt
Ralf Schluter
Hermann Ney
AI4TSMedIm
262
53
0
19 May 2020
You Do Not Need More Data: Improving End-To-End Speech Recognition by
  Text-To-Speech Data Augmentation
You Do Not Need More Data: Improving End-To-End Speech Recognition by Text-To-Speech Data Augmentation
A. Laptev
Roman Korostik
A. Svischev
A. Andrusenko
Ivan Medennikov
S. Rybin
309
67
0
14 May 2020
1
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