My picture from long ago

Hello there! Welcome to my personal portfolio!

I am Iftekhar Tanveer—a computer scientist interested in natural language processing and machine learning. In short, I like to make computers understand human language.

I work as a research scientist at Spotify Research. My primary role there is to come up with convenient techniques to make computers understand the conversations that are happening within the podcasts!

Podcasts are actually billions of hours of speech audio where people are talking in more than 100 different languages. My job is to teach computers to make sense of all those conversations. I can speak only two languages (English and Bengali) and I can focus to listen to only about an hour-long audio per day. Do you think my job is something feasible to do? Send me what you think about it using the Contact Me page.

I did my Ph.D. at the University of Rochester. My academic advisor was Professor M. Ehsan Hoque. Beside my extraordinary advisor, I was also humbled by getting the opportunity to work with several other amazing researchers and reputed professors, including Professor Henry Kautz, Professor Daniel Gildea, Professor Ji Liu, and Professor Gonzalo Mateos. I am originally from Bangladesh.

Highlighted Publications

Unsupervised Speaker Diarization that is Agnostic to Language, Overlap-Aware, and Tuning Free, Interspeech’22, Incheon, Korea
FairyTED: A Fair Rating Predictor for TED Talk Data, AAAI’20, NY, USA
UR-FUNNY: A Multimodal Language Dataset for Understanding Humor, EMNLP’19, Hong Kong, China
A Causality-Guided Prediction of the TED Talk Ratings from the Speech-Transcripts using Neural Networks
, arXiv preprint arXiv:1905.08392
SyntaViz: Visualizing Voice Queries through a Syntax-Driven Hierarchical Ontology, EMNLP’18, Brussels, Belgium, 2018 
Awe the Audience: How the Narrative Trajectories Affect Audience Perception in Public Speaking
, CHI’18, Montreal, Canada, 2018
AutoManner: An Automated Interface for Making Public Speakers Aware of Their Mannerisms, IUI’16, Sonoma, CA, USA, 2016
Unsupervised Extraction of Human-Interpretable Nonverbal Behavioral Cues in a Public Speaking Scenario, ACMMM’15, Brisbane, Australia, 2015
Automated Prediction of Job Interview Performance: The Role of What You Say and How You Say It, FG’15, Ljubljana, Slovenia, 2015.

News and Presentations

 June 15th, 2022My first paper after joining Spotify has been accepted for presentation at Interspeech 2022. It is a paper on speaker diarization, which is the problem of identifying “who spoke where” in long audio. In this paper, we propose a speaker diarization technique that is agnostic to language, overlap-aware, and tuning free.paper
Aug 3rd, 2020I joined Spotify as a research scientist 
Nov 10th, 2019Our FairyTED paper got accepted in AAAI 2020!!! After reading Judea Pearl’s “The Book of Why”, I realized that neural networks alone can’t do a bias-free and fair prediction. It is important to model the data generating process (possibly using causal models). I tried to convince Rupam, Ankani, and Soumen regarding the importance of the problem and, together, we pulled the paper off. I’m really very proud of this contribution.paper
Aug 13th, 2019Our UR-Funny paper got accepted in EMNLP 2019paper
Oct 27th, 2018I presented in the lab on Judea Pearl’s new book “The Book of Why”. My advisor, Ehsan Hoque tweeted that and Judea Pearl himself commented on that tweet!Tweet
Oct 22nd, 2018I’ve successfully defended my PhD thesisPictures
Aug 6th, 2018One of my work during the internship in Comcast Lab is accepted in EMNLP 2018Paper
April 25, 2018I presented our TED Talk work in CHI 2018Slides
Feb 16, 2018I presented Chapter 5 from the Deep Learning book in LabSlides
Jan 2018Our paper got accepted in CHI 2018 

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