Dr. Shammur Absar Chowdhury
Scientist
Educational Qualifications
PhD in Computer Science
Bachelor of Science in Electronics and Communication Engineering, with 2nd major in Bachelor of Science in Computer Science
Entity
Qatar Computing Research Institute
Divison
Arabic Language Technologies
Biography
Dr. Chowdhury specializes in designing Conversational AI models, primarily addressing complex challenges such as multispeaker interactions, nuanced multilingual and dialect variations, and code-switching, among various other intricate conversational dynamics. She is currently the leading (PI) on the QVoice project, which empowers speakers—both native and non-native of all ages alike—to learn spoken Arabic. The QVoice project leverages adaptive speech technologies and multimodal feedback modules as its underlying technologies. Dr. Chowdhury has received numerous awards and grants, including the NVIDIA Academic Hardware Grant for her research in simulating human language learning capabilities using DNN-based language models, a study that was also conducted as a part of the TRAILs project, funded by PRIN MIUR. As a key contributor to the EU-funded projects SENSEI and PortDial, Dr. Chowdhury developed conversational models adept at understanding human conversation, facilitating automatic summarization and mental health screening. She authored over 60 peer-reviewed publications in top-tier conferences and journals and played an active role in the research community by organizing shared tasks, challenges, and workshops, as well as serving on the committees of top-tier conferences and special interest groups. She co-founded the Bangla Language Processing Community and MyVoice, a crowdsourced platform, designed to bridge the gaps between standard and dialectal Arabic resources.
PhD in Computer Science
ICT Doctoral School, University of Trento, Italy
Nov-2012 to April-2017
Bachelor of Science in Electronics and Communication Engineering, with 2nd major in Bachelor of Science in Computer Science
BRAC University, Bangladesh
Jan-2007 to Dec-2010
- Multilingual and multi-view representation learning
- Conversational AI
- Non-Verbal Communication
- Spoken Language Processing
- Natural Language Processing
Scientist
Qatar Computing Research Institute (QCRI)
October 2021 - Present
Postdoctoral Researcher
Qatar Computing Research Institute (QCRI)
May 2019 - September 2021
Postdoctoral Researcher
Center for Mind/Brain Sciences (CIMEC), University of Trento
June 2017 - April 2019
PhD Researcher Signals and Interactive Systems Lab (SIS Lab)
University of Trento
November 2012 - April 2017
Research Assistant
Signals and Interactive Systems Lab (SIS Lab), University of Trento
March 2012 - October 2012
Lecturer
Department of Computer Science and Engineering, BRAC University
January 2011 - February 2012
Senior Research Assistant
Center for Research on Bangla Language Processing (CRBLP), BRAC University
October 2010 - February 2012
- Chowdhury, S. A., Durrani, N., & Ali, A. (2023). What do end-to-end speech models learn about speaker, language and channel information? A layer-wise and neuron-level analysis. Computer Speech & Language, 83, 101539.
- Kheir, Y. E., Chowdhury, S. A., & Ali, A. (2023). Multi-View Multi-Task Representation Learning for Mispronunciation Detection. Speech and Language Processing Tools in Education.
- Chowdhury, S. A., Hussein, A., Abdelali, A., & Ali, A. (2021). Towards one model to rule all: Multilingual strategy for dialectal code-switching Arabic ASR. arXiv preprint arXiv:2105.14779.
- Chowdhury, S. A., Stepanov, E. A., Danieli, M., & Riccardi, G. (2019). Automatic classification of speech overlaps: feature representation and algorithms. Computer Speech & Language, 55, 145-167.
- Chowdhury, S. A., Stepanov, E. A., & Riccardi, G. (2016). Predicting User Satisfaction from Turn-Taking in Spoken Conversations. In Interspeech (pp. 2910-2914).
- Complete Publication Listing(s): Google Scholar