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. I work as a Research Scientist at Spotify Research.

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

Highlighted Publications

Lightweight and Efficient Spoken Language Identification of Long-form Audio, Interspeech’23, Dublin, Ireland
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

Aug 21st, 2023My second paper at Spotify is published at Interspeech 2023. It is on Spoken Language Identification (SLI) for podcasts. SLI is a task of identifying what language being spoken from audio only. Our method is applicable to really long audios (e.g. podcasts) and allows multiple languages being spoken in the same audio.Paper,
Spotify blog
 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,
Spotify blog
Aug 3rd, 2020I joined Spotify as a research scientist 
Nov 10th, 2019Our FairyTED paper was 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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