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20202026
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cs.CL2026

NAVER LABS Europe Submission to the Instruction-following 2026 Short Track

Marcely Zanon Boito, Hemant Yadav, Jean-Luc Meunier +1

In this paper, we describe NAVER LABS Europe's submission to the instruction-following speech processing short track at IWSLT 2026. We participate again in the constrained setting,…

cs.CL2024

JOOCI: a Framework for Learning Comprehensive Speech Representations

Hemant Yadav, Rajiv Ratn Shah, Sunayana Sitaram

Information in speech can be categorized into two groups: Content (what is being said, such as linguistics) and Other (how it is expressed such as information about speaker and par…

cs.CL2024

Speech Representation Learning Revisited: The Necessity of Separate Learnable Parameters and Robust Data Augmentation

Hemant Yadav, Sunayana Sitaram, Rajiv Ratn Shah

Speech modeling methods learn one embedding for a fixed segment of speech, typically in between 10-25 ms. The information present in speech can be divided into two categories: "wha…

cs.CL2024

MS-HuBERT: Mitigating Pre-training and Inference Mismatch in Masked Language Modelling methods for learning Speech Representations

Hemant Yadav, Sunayana Sitaram, Rajiv Ratn Shah

In recent years, self-supervised pre-training methods have gained significant traction in learning high-level information from raw speech. Among these methods, HuBERT has demonstra…

cs.CL2022

A Survey of Multilingual Models for Automatic Speech Recognition

Hemant Yadav, Sunayana Sitaram

Although Automatic Speech Recognition (ASR) systems have achieved human-like performance for a few languages, the majority of the world's languages do not have usable systems due t…

cs.CL2021

Cisco at AAAI-CAD21 shared task: Predicting Emphasis in Presentation Slides using Contextualized Embeddings

Sreyan Ghosh, Sonal Kumar, Harsh Jalan +2

This paper describes our proposed system for the AAAI-CAD21 shared task: Predicting Emphasis in Presentation Slides. In this specific task, given the contents of a slide we are ask…