Trung Ngo Trong

According to our database1, Trung Ngo Trong authored at least 14 papers between 2016 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
The Transitive Information Theory and its Application to Deep Generative Models.
CoRR, 2022

2021
Voxceleb Enrichment for Age and Gender Recognition.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021

2020
Maximal Figure-of-Merit Framework to Detect Multi-Label Phonetic Features for Spoken Language Recognition.
IEEE ACM Trans. Audio Speech Lang. Process., 2020

Semisupervised Generative Autoencoder for Single-Cell Data.
J. Comput. Biol., 2020

2019
I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences.
CoRR, 2019

Towards Debugging Deep Neural Networks by Generating Speech Utterances.
Proceedings of the Interspeech 2019, 2019

2018
Staircase Network: structural language identification via hierarchical attentive units.
Proceedings of the Odyssey 2018: The Speaker and Language Recognition Workshop, 2018

Enabling Spoken Dialogue Systems for Low-Resourced Languages - End-to-End Dialect Recognition for North Sami.
Proceedings of the 9th International Workshop on Spoken Dialogue System Technology, 2018

2016
Fantastic 4 system for NIST 2015 Language Recognition Evaluation.
CoRR, 2016

Deep Language: a comprehensive deep learning approach to end-to-end language recognition.
Proceedings of the Odyssey 2016: The Speaker and Language Recognition Workshop, 2016

The 2015 NIST Language Recognition Evaluation: The Shared View of I2R, Fantastic4 and SingaMS.
Proceedings of the Interspeech 2016, 2016

Variation in Spoken North Sami Language.
Proceedings of the Interspeech 2016, 2016

Body movements and laughter recognition: experiments in first encounter dialogues.
Proceedings of the Workshop on Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction, 2016

LifeLine Dialogues with Roberta.
Proceedings of the Future and Emerging Trends in Language Technology. Machine Learning and Big Data, 2016


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