1 citations · 1 across the 10 of their papers we have counts for
13 papers
DirectSpeech2LLM: A Simple End-to-End Framework to Mitigate Prompt Overfitting in Speech-LLMs
Hemant Yadav, Sunayana Sitaram, Roger Zimmermann +1
Speech-LLMs often exhibit prompt overfitting, where models solely trained on automatic speech recognition (ASR) instruction fail to generalize to new instructions such as speech tr…
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,…
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…
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…
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…
Partial Rank Similarity Minimization Method for Quality MOS Prediction of Unseen Speech Synthesis Systems in Zero-Shot and Semi-supervised setting
Hemant Yadav, Erica Cooper, Junichi Yamagishi +2
This paper introduces a novel objective function for quality mean opinion score (MOS) prediction of unseen speech synthesis systems. The proposed function measures the similarity o…
Analysing the Masked predictive coding training criterion for pre-training a Speech Representation Model
Hemant Yadav, Sunayana Sitaram, Rajiv Ratn Shah
Recent developments in pre-trained speech representation utilizing self-supervised learning (SSL) have yielded exceptional results on a variety of downstream tasks. One such techni…
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…
Intent Classification Using Pre-trained Language Agnostic Embeddings For Low Resource Languages
Hemant Yadav, Akshat Gupta, Sai Krishna Rallabandi +2
Building Spoken Language Understanding (SLU) systems that do not rely on language specific Automatic Speech Recognition (ASR) is an important yet less explored problem in language…
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…
mask-Net: Learning Context Aware Invariant Features using Adversarial Forgetting (Student Abstract)
Hemant Yadav, Atul Anshuman Singh, Rachit Mittal +3
Training a robust system, e.g.,Speech to Text (STT), requires large datasets. Variability present in the dataset such as unwanted nuisances and biases are the reason for the need o…
MIDAS at SemEval-2020 Task 10: Emphasis Selection using Label Distribution Learning and Contextual Embeddings
Sarthak Anand, Pradyumna Gupta, Hemant Yadav +4
This paper presents our submission to the SemEval 2020 - Task 10 on emphasis selection in written text. We approach this emphasis selection problem as a sequence labeling task wher…
End-to-end Named Entity Recognition from English Speech
Hemant Yadav, Sreyan Ghosh, Yi Yu +1
Named entity recognition (NER) from text has been a widely studied problem and usually extracts semantic information from text. Until now, NER from speech is mostly studied in a tw…