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Egor Lakomkin
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The OMG-emotion behavior dataset
P Barros, N Churamani, E Lakomkin, H Siqueira, A Sutherland, S Wermter
2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018
1172018
On the robustness of speech emotion recognition for human-robot interaction with deep neural networks
E Lakomkin, MA Zamani, C Weber, S Magg, S Wermter
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
572018
Reusing neural speech representations for auditory emotion recognition
E Lakomkin, C Weber, S Magg, S Wermter
arXiv preprint arXiv:1803.11508, 2018
422018
Prompting large language models with speech recognition abilities
Y Fathullah, C Wu, E Lakomkin, J Jia, Y Shangguan, K Li, J Guo, W Xiong, ...
arXiv preprint arXiv:2307.11795, 2023
292023
Incorporating end-to-end speech recognition models for sentiment analysis
E Lakomkin, MA Zamani, C Weber, S Magg, S Wermter
2019 International Conference on Robotics and Automation (ICRA), 7976-7982, 2019
252019
Emorl: continuous acoustic emotion classification using deep reinforcement learning
E Lakomkin, MA Zamani, C Weber, S Magg, S Wermter
2018 IEEE International Conference on Robotics and Automation (ICRA), 4445-4450, 2018
242018
GradAscent at EmoInt-2017: character-and word-level recurrent neural network models for tweet emotion intensity detection
E Lakomkin, C Bothe, S Wermter
arXiv preprint arXiv:1803.11509, 2018
222018
KT-speech-crawler: Automatic dataset construction for speech recognition from YouTube videos
E Lakomkin, S Magg, C Weber, S Wermter
arXiv preprint arXiv:1903.00216, 2019
212019
Subword regularization: An analysis of scalability and generalization for end-to-end automatic speech recognition
E Lakomkin, J Heymann, I Sklyar, S Wiesler
arXiv preprint arXiv:2008.04034, 2020
102020
Synthvsr: Scaling up visual speech recognition with synthetic supervision
X Liu, E Lakomkin, K Vougioukas, P Ma, H Chen, R Xie, M Doulaty, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
72023
Combining articulatory features with end-to-end learning in speech recognition
L Qu, C Weber, E Lakomkin, J Twiefel, S Wermter
Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018
72018
Анализ статистических алгоритмов снятия морфологической омонимии в русском языке
ЕД Лакомкин, ИВ Пузыревский, ДА Рыжова
URL: http://aistconf. org/stuff/aist2013/submissions/aist2013_submission_33. pdf, 2013
62013
Automatically augmenting an emotion dataset improves classification using audio
E Lakomkin, C Weber, S Wermter
EACL 2017, 194, 2017
52017
On the robustness of speech emotion recognition for human-robot interaction with deep neural networks. In 2018 IEEE
E Lakomkin, MA Zamani, C Weber, S Magg, S Wermter
RSJ International Conference on Intelligent Robots and Systems (IROS), 854-860, 0
5
Predictive Auxiliary Variational Autoencoder for Representation Learning of Global Speech Characteristics.
S Springenberg, E Lakomkin, C Weber, S Wermter
INTERSPEECH, 934-938, 2019
42019
End-to-End Speech Recognition Contextualization with Large Language Models
E Lakomkin, C Wu, Y Fathullah, O Kalinli, ML Seltzer, C Fuegen
arXiv preprint arXiv:2309.10917, 2023
32023
Image-to-Text Transduction with Spatial Self-Attention.
S Springenberg, E Lakomkin, C Weber, S Wermter
ESANN, 2018
22018
Egocentric audio-visual noise suppression
R Sharma, W He, J Lin, E Lakomkin, Y Liu, K Kalgaonkar
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
12023
Методы и практики проектирования web-приложений реального времени с использованием технологии java
ЕД Лакомкин
RSDN Magazine, 34-38, 2012
12012
Towards General-Purpose Speech Abilities for Large Language Models Using Unpaired Data
Y Fathullah, C Wu, E Lakomkin, J Jia, Y Shangguan, J Mahadeokar, ...
arXiv preprint arXiv:2311.06753, 2023
2023
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