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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Blog Post number 4
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Blog Post number 1
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portfolio
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publications
A survey of breast cancer screening techniques: thermography and electrical impedance tomography
Published in Journal of Medical Engineering & Technology, 2019
This work aims to review the last breakthroughs about thermography, infra-red imaging and electrical impedance tomography for breast cancer diagnosis. Additionally, we explore the main benefits of integrating computational skills. We provide a comparison between several machine learning techniques applied to breast cancer diagnosis going from logistic regression, decision trees and random forest to artificial, deep and convolutional neural networks. Finally, it is mentioned several recommendations for 3D breast simulations, pre-processing techniques, biomedical devices in the research field, prediction of tumour location and size.
Recommended citation: Zuluaga-Gomez, J., Zerhouni, N., Al Masry, Z., Devalland, C. and Varnier, C., 2019. A survey of breast cancer screening techniques: thermography and electrical impedance tomography. Journal of medical engineering & technology, 43(5), pp.305-322. https://www.tandfonline.com/doi/abs/10.1080/03091902.2019.1664672
A portable breast cancer detection system based on smartphone with infrared camera
Published in Vibroengineering PROCEDIA, Vol. 26, 2019
The traditional detection methods have the disadvantages of radiation exposure, high cost, and shortage of medical resources, which restrict the popularity of early screening for breast cancer. An inexpensive, accessible, and friendly way to detect is urgently needed. Infrared thermography, an emerging means to breast cancer detection, is extremely sensitive to tissue abnormalities caused by inflammation and vascular proliferation. In this work, combined with the temperature and texture features, we designed a breast cancer detection system based on smart phone with infrared camera.
Recommended citation: Ma, J., Shang, P., Lu, C., Meraghni, S., Benaggoune, K., Zuluaga, J., Zerhouni, N., Devalland, C. and Al Masry, Z., 2019. A portable breast cancer detection system based on smartphone with infrared camera. Vibroengineering PROCEDIA, 26, pp.57-63. https://www.jvejournals.com/article/20978
Techniques for water disinfection, decontamination and desalinization: A review
Published in Desalination and Water Treatment, 2020
The review begins with a short presentation of the first explored water purification techniques starting from the Bronze Age, then, it is presented the minimum quality parameters and comments that disinfection, decontamination, and desalinization of wastewater and seawater must achieve. It is also reviewed several water purification methods based on microbiological, chemical and physical techniques. This review conveys a fine reviewing of solar stills, solar collectors and heterogeneous photocatalysis, presenting characteristics and latest innovations from several researchers.
Recommended citation: Zuluaga-Gomez, J., Bonaveri, P., Zuluaga, D., Álvarez-Peña, C. and Ramirez-Ortiz, N., 2020. Techniques for water disinfection, decontamination and desalinization: A review. Desalin. WATER Treat, 181, pp.47-63. https://www.deswater.com/DWT_articles/vol_181_papers/181_2020_47.pdf
Automatic Speech Recognition Benchmark for Air-Traffic Communications
Published in Interspeech 2020, 2020
This paper is about the Automatic Speech Recognition for Air-traffic Control Communications
Recommended citation: Zuluaga-Gomez, J., Motlicek, P., Zhan, Q., Veselý, K., Braun, R. (2020) Automatic Speech Recognition Benchmark for Air-Traffic Communications. Proc. Interspeech 2020, 2297-2301, doi: 10.21437/Interspeech.2020-2173. https://isca-speech.org/archive/interspeech_2020/zuluagagomez20_interspeech.html
Pkwrap: a PyTorch Package for LF-MMI Training of Acoustic Models
Published in ArXiv preprint, 2020
Pkwrap (short form of PyTorch Kaldi WRapper) is a simple wrapper that is useful to train acoustic models in PyTorch using Kaldi’s LF-MMI training framework. The wrapper, enables the user to utilize the flexibility provided by PyTorch in designing model architectures. It exposes the LF-MMI cost function as an autograd function.
Recommended citation: Madikeri, S., Tong, S., Zuluaga-Gomez, J., Vyas, A., Motlicek, P. and Bourlard, H., 2020. Pkwrap: a pytorch package for lf-mmi training of acoustic models. arXiv preprint arXiv:2010.03466. https://arxiv.org/abs/2010.03466
A CNN-based methodology for breast cancer diagnosis using thermal images
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2020
Currently, mammography, magnetic resonance imaging, ultrasound, and biopsies are the main screening techniques, which require either, expensive devices or personal qualified; but some countries still lack access due to economic, social, or cultural issues. As an alternative diagnosis methodology for breast cancer, this study presents a computer-aided diagnosis system based on convolutional neural networks (CNN) using thermal images. We demonstrate that CNNs are faster, reliable and robust when compared with different techniques. We study the influence of data pre-processing, data augmentation and database size on several CAD models.
Recommended citation: Zuluaga-Gomez, J., Al Masry, Z., Benaggoune, K., Meraghni, S. and Zerhouni, N., 2021. A CNN-based methodology for breast cancer diagnosis using thermal images. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 9(2), pp.131-145. https://www.tandfonline.com/doi/abs/10.1080/21681163.2020.1824685
Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications
Published in Proceedings of 8th OpenSky Symposium 2020, 2020
This paper is about the Automatic Speech Recognition for Air-traffic Control Communications
Recommended citation: Zuluaga-Gomez, J.; Veselý, K.; Blatt, A.; Motlicek, P.; Klakow, D.; Tart, A.; Szöke, I.; Prasad, A.; Sarfjoo, S.; Kolčárek, P.; Kocour, M.; Černocký, H.; Cevenini, C.; Choukri, K.; Rigault, M.; Landis, F. Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications. Proceedings 2020, 59, 14. https://doi.org/10.3390/proceedings2020059014 https://www.mdpi.com/2504-3900/59/1/14
Boosting of Contextual Information in ASR for Air-Traffic Call-Sign Recognition
Published in Interspeech 2021, 2021
This paper is about the Automatic Speech Recognition for Air-traffic Control Communications
Recommended citation: Kocour, M., Veselý, K., Blatt, A., Gomez, J.Z., Szöke, I., Černocký, J., Klakow, D., Motlicek, P. (2021) Boosting of Contextual Information in ASR for Air-Traffic Call-Sign Recognition. Proc. Interspeech 2021, 3301-3305, doi: 10.21437/Interspeech.2021-1619. https://isca-speech.org/archive/interspeech_2021/kocour21_interspeech.html
Contextual Semi-Supervised Learning: An Approach to Leverage Air-Surveillance and Untranscribed ATC Data in ASR Systems
Published in Interspeech 2021, 2021
This paper is about the Automatic Speech Recognition for Air-traffic Control Communications
Recommended citation: Zuluaga-Gomez, J., Nigmatulina, I., Prasad, A., Motlicek, P., Veselý, K., Kocour, M., Szöke, I. (2021) Contextual Semi-Supervised Learning: An Approach to Leverage Air-Surveillance and Untranscribed ATC Data in ASR Systems. Proc. Interspeech 2021, 3296-3300, doi: 10.21437/Interspeech.2021-1373. https://isca-speech.org/archive/interspeech_2021/zuluagagomez21_interspeech.html
Grammar Based Identification Of Speaker Role For Improving ATCO And Pilot ASR
Published in ArXiv, 2021
This paper is about the Automatic Speech Recognition for Air-traffic Control Communications
Recommended citation: Prasad, A., Zuluaga-Gomez, J., Motlicek, P., Ohneiser, O., Helmke, H., Sarfjoo, S. and Nigmatulina, I., 2021. Grammar Based Identification Of Speaker Role For Improving ATCO And Pilot ASR. arXiv preprint arXiv:2108.12175. https://arxiv.org/abs/2108.12175
Improving callsign recognition with air-surveillance data in air-traffic communication
Published in ArXiv, 2021
This paper is about the Automatic Speech Recognition in Air-traffic Control Communications
Recommended citation: Nigmatulina, I., Braun, R., Zuluaga-Gomez, J. and Motlicek, P., 2021. Improving callsign recognition with air-surveillance data in air-traffic communication. arXiv preprint arXiv:2108.12156. https://arxiv.org/abs/2108.12156
Domain-Adversarial Based Model with Phonological Knowledge for Cross-Lingual Speech Recognition
Published in Electronics, 2021
This paper is about cross-lingual speech recognition
Recommended citation: Zhan, Q.; Xie, X.; Hu, C.; Zuluaga-Gomez, J.; Wang, J.; Cheng, H. Domain-Adversarial Based Model with Phonological Knowledge for Cross-Lingual Speech Recognition. Electronics 2021, 10, 3172. https://doi.org/10.3390/electronics10243172 https://www.mdpi.com/2079-9292/10/24/3172
A two-step approach to leverage contextual data: speech recognition in air-traffic communications
Published in 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing, 2022
This paper is about the Automatic Speech Recognition in Air-traffic Control Communications
Recommended citation: Nigmatulina, Iuliia and Zuluaga-Gomez, Juan and Prasad, Amrutha and Saeed Sarfjoo, Seyyed and Motlicek, Petr. (2022). A two-step approach to leverage contextual data: Speech recognition in air-traffic communications. ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing, 6282–6286 https://arxiv.org/abs/2202.03725
BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communications
Published in IEEE SLT 2022, 2022
This paper is about Automatic Speech Recognition in Air-traffic Control Communications
Recommended citation: Juan Zuluaga-Gomez, Seyyed Saeed Sarfjoo, Amrutha Prasad, Iuliia Nigmatulina, Petr Motlicek, Karel Ondrej, Oliver Ohneiser, Hartmut Helmke, 2022. BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communications. 2022 IEEE Spoken Language Technology Workshop (SLT), Doha, Qatar. https://arxiv.org/abs/2110.05781
IDIAPers - Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot Approach
Published in CASE - EMNLP 2022 (5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text), 2022
In this paper, we describe our participation in the subtask 1 of CASE-2022 (at EMNLP), Event Causality Identification with Casual News Corpus
Recommended citation: Burdisso, Sergio and Zuluaga-Gomez, Juan and Villatoro-Tello, Esau and Fajcik, Martin and Singh, Muskaan and Smrz, Pavel and Motlicek, Petr, 2022. IDIAPers - Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot Approach. The 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE - EMNLP 2022). Association for Computational Linguistics https://arxiv.org/abs/2209.03895
IDIAPers - Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model
Published in CASE - EMNLP 2022 (5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text), 2022
In this paper, we describe our participation in the subtask 2 of CASE-2022 (at EMNLP), Event Causality Identification with Casual News Corpus
Recommended citation: Fajcik, Martin and Singh, Muskaan and Zuluaga-Gomez, Juan and Villatoro-Tello, Esau and Burdisso, Sergio and Motlicek, Petr and Smrz, Pavel, 2022. IDIAPers - Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model. The 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE - EMNLP 2022). Association for Computational Linguistics https://arxiv.org/abs/2209.03891
How Does Pre-trained Wav2Vec 2.0 Perform on Domain Shifted ASR? An Extensive Benchmark on Air Traffic Control Communications
Published in IEEE SLT 2022, 2022
This paper is about Automatic Speech Recognition in air traffic Control Communications
Recommended citation: Juan Zuluaga-Gomez, Amrutha Prasad, Iuliia Nigmatulina, Saeed Sarfjoo, Petr Motlicek, Matthias Kleinert, Hartmut Helmke, Oliver Ohneiser, Qingran Zhan, 2022. How Does Pre-trained Wav2Vec 2.0 Perform on Domain Shifted ASR? An Extensive Benchmark on Air Traffic Control Communications. 2022 IEEE Spoken Language Technology Workshop (SLT), Doha, Qatar. https://arxiv.org/abs/2203.16822
talks
An introduction to speech-based technologies for Natural Language Processing applications
Published:
Since the last two decades, the amount of data generated and collected has grown exponentially, and especially through the rise of unstructured data such as images, videos or text. More recently, audio and speech data have gained a large interest, for example through voice assistants. Companies like Google, Facebook, Apple, and Amazon have shown an increasing interest in professionals with skills and tools for ‘understanding’ and ‘transforming’ the massive flow of speech data in relevant information. Some of the most important speech-based technologies are voice activity detection, speaker diarization and identification, and automatic speech recognition. These techologies are often used as an input to various NLP applications afterwards. This brief workshop will give you a set of basic tools for grasping the main aspects of speech-based technologies and how they can be implemented in real-life cases.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.