Juan Pablo Zuluaga

Juan Pablo Zuluaga

PhD Student | École polytechnique fédérale de Lausanne ‐ EPFL

Posts by Collection

portfolio

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

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.