This image shows Pavel Denisov

Pavel Denisov

PhD Student
Institut für maschinelle Sprachverarbeitung
Digital Phonetics

Contact

Deutschland

Office Hours

As needed, write me an e-mail.

2022

  • S. Arora, S. Dalmia, P. Denisov, X. Chang, Y. Ueda, Y. Peng, Y. Zhang, S. Kumar, K. Ganesan, B. Yan, N. T. Vu, A. W. Black, S. Watanabe. ESPnet-SLU: Advancing Spoken Language Understanding through ESPnet. In Proceedings of the 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
  • I. Hamed, P. Denisov, C. Y. Li, M. Elmahdy, S. Abdennadher, N. T. Vu. Investigations on speech recognition systems for low-resource dialectal Arabic–English code-switching speech. In Computer Speech & Language,
    Volume 72.

2021

  • P. Denisov, M. Mager, N. T. Vu. IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task. In Proceedings of the International Conference on Spoken Language Translation (IWSLT), 2021.
  • D. Raj, P. Denisov, Z. Chen, H. Erdogan, Z. Huang, M. He, S. Watanabe, J. Du, T. Yoshioka, Y. Luo, N. Kanda, J. Li, S. Wisdom, J. R. Hershey. Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis. In Proceedings of the 8th IEEE Spoken Language Technology Workshop (SLT), 2021.

2020

  • P. Denisov and N. T. Vu. Pretrained Semantic Speech Embeddings for End-to-End Spoken Language Understanding via Cross-Modal Teacher-Student Learning. In Proceedings of Interspeech, 2020.
  • C. Y. Li, D. Ortega, D. Väth, F. Lux, L. Vanderlyn, M. Schmidt, M. Neumann, M. Völkel, P. Denisov, S. Jenne, Z. Kacarevic and N. T. Vu. ADVISER: A Toolkit for Developing Multimodal, Multi-domain and Socially-engaged Conversational Agents. In Proceedings of ACL - Systems Demonstration, 2020.

2019

  • P. Denisov and N. T. Vu. End-to-End Multi-Speaker Speech Recognition using Speaker Embeddings and Transfer Learning. In Proceedings of Interspeech, 2019.
  • D. Ortega, C. Y. Li, G. Vallejo, P. Denisov, N. T. Vu. Context-aware Neural-based Dialog Act Classification On Automatically Generated Transcriptions. In Proceedings of the 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019.
  • P. Denisov and N. T. Vu. IMS-Speech: A Speech to Text Tool. In Proceedings of the 30th Conference on Electronic Speech Signal Processing (ESSV), 2019.

2018

  • P. Denisov, N. T. Vu and M. Ferras. Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition. In Proceedings of the 13th ITG Conference on Speech Communication, 2018.

SS 2022 Team Laboratory Phonetics
WS 2021/22
Speech Recognition
SS 2021 
Team Laboratory Phonetics
WS 2020/21
Speech Recognition
SS 2020
Team Laboratory Phonetics
SS 2019
Spoken Language Processing

Since 08.2018:
PhD candidate in Digital Phonetics, Institute for Natural Language Processing (IMS),University of Stuttgart

10.2017 - 07.2018:
Master Thesis Student, Working Student, Sony Stuttgart Technology Center

10.2016 - 07.2018:
MSc. in Computational Linguistics, Institute for Natural Language Processing (IMS),University of Stuttgart
Thesis: Transfer Learning for Robust Acoustic Modeling in Automatic Speech Recognition

11.2006 - 10.2016:
Software Engineer, Scoros International Inc.
Document Processing, Content Extraction, Release Engineering

09.2003 - 02.2009:
Diploma of Engineer, Saint Petersburg State University of Aerospace Instrumentation
Computer Aided Engineering

To the top of the page