activity
20192025
most citedDating Documents using Graph Convolution Networks

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

eess.AS2025

Continuous-Token Diffusion for Speaker-Referenced TTS in Multimodal LLMs

Xinlu He, Swayambhu Nath Ray, Harish Mallidi +5

Unified architectures in multimodal large language models (MLLM) have shown promise in handling diverse tasks within a single framework. In the text-to-speech (TTS) task, current M…

cs.CL2022

Unified Modeling of Multi-Domain Multi-Device ASR Systems

Soumyajit Mitra, Swayambhu Nath Ray, Bharat Padi +6

Modern Automatic Speech Recognition (ASR) systems often use a portfolio of domain-specific models in order to get high accuracy for distinct user utterance types across different d…

eess.AS2021

Improving RNN-T ASR Performance with Date-Time and Location Awareness

Swayambhu Nath Ray, Soumyajit Mitra, Raghavendra Bilgi +1

In this paper, we explore the benefits of incorporating context into a Recurrent Neural Network (RNN-T) based Automatic Speech Recognition (ASR) model to improve the speech recogni…

eess.AS2021

Listen with Intent: Improving Speech Recognition with Audio-to-Intent Front-End

Swayambhu Nath Ray, Minhua Wu, Anirudh Raju +7

Comprehending the overall intent of an utterance helps a listener recognize the individual words spoken. Inspired by this fact, we perform a novel study of the impact of explicitly…

cs.CL2021

Timestamping Documents and Beliefs

Swayambhu Nath Ray

Most of the textual information available to us are temporally variable. In a world where information is dynamic, time-stamping them is a very important task. Documents are a good…

cs.CL2019★ 1 cited

Dating Documents using Graph Convolution Networks

Shikhar Vashishth, Shib Sankar Dasgupta, Swayambhu Nath Ray +1

Document date is essential for many important tasks, such as document retrieval, summarization, event detection, etc. While existing approaches for these tasks assume accurate know…