341 citations · 501 across the 66 of their papers we have counts for
13 papers · 1 filter
BiG-SURE - Bipartite Graph for Semantic Uncertainty and Reliability Estimation of LLMs
Debarpan Bhattacharya, Malay Phadke, Sriram Ganapathy
Reliable uncertainty estimation is a crucial requirement for deploying large language models (LLMs) and vision-language models (VLMs) in safety-critical settings, especially when t…
A Mixture-of-Experts Model for Multimodal Emotion Recognition in Conversations
Soumya Dutta, Smruthi Balaji, Sriram Ganapathy
Emotion Recognition in Conversations (ERC) presents unique challenges, requiring models to capture the temporal flow of multi-turn dialogues and to effectively integrate cues from…
Benchmarking and Confidence Evaluation of LALMs For Temporal Reasoning
Debarpan Bhattacharya, Apoorva Kulkarni, Sriram Ganapathy
The popular success of text-based large language models (LLM) has streamlined the attention of the multimodal community to combine other modalities like vision and audio along with…
Spoken Language Understanding on Unseen Tasks With In-Context Learning
Neeraj Agrawal, Sriram Ganapathy
Spoken language understanding (SLU) tasks involve diverse skills that probe the information extraction, classification and/or generation capabilities of models. In this setting, ta…
STAB: Speech Tokenizer Assessment Benchmark
Shikhar Vashishth, Harman Singh, Shikhar Bharadwaj +6
Representing speech as discrete tokens provides a framework for transforming speech into a format that closely resembles text, thus enabling the use of speech as an input to the wi…
Improving Self-supervised Pre-training using Accent-Specific Codebooks
Darshan Prabhu, Abhishek Gupta, Omkar Nitsure +2
Speech accents present a serious challenge to the performance of state-of-the-art end-to-end Automatic Speech Recognition (ASR) systems. Even with self-supervised learning and pre-…
Towards the Next Frontier in Speech Representation Learning Using Disentanglement
Varun Krishna, Sriram Ganapathy
The popular frameworks for self-supervised learning of speech representations have largely focused on frame-level masked prediction of speech regions. While this has shown promisin…
Self-Influence Guided Data Reweighting for Language Model Pre-training
Megh Thakkar, Tolga Bolukbasi, Sriram Ganapathy +3
Language Models (LMs) pre-trained with self-supervision on large text corpora have become the default starting point for developing models for various NLP tasks. Once the pre-train…
Accented Speech Recognition With Accent-specific Codebooks
Darshan Prabhu, Preethi Jyothi, Sriram Ganapathy +1
Speech accents pose a significant challenge to state-of-the-art automatic speech recognition (ASR) systems. Degradation in performance across underrepresented accents is a severe d…
Multimodal Modeling For Spoken Language Identification
Shikhar Bharadwaj, Min Ma, Shikhar Vashishth +10
Spoken language identification refers to the task of automatically predicting the spoken language in a given utterance. Conventionally, it is modeled as a speech-based language ide…
Label Aware Speech Representation Learning For Language Identification
Shikhar Vashishth, Shikhar Bharadwaj, Sriram Ganapathy +5
Speech representation learning approaches for non-semantic tasks such as language recognition have either explored supervised embedding extraction methods using a classifier model…
Leveraging Native Language Speech for Accent Identification using Deep Siamese Networks
Aditya Siddhant, Preethi Jyothi, Sriram Ganapathy
The problem of automatic accent identification is important for several applications like speaker profiling and recognition as well as for improving speech recognition systems. The…
The IBM Speaker Recognition System: Recent Advances and Error Analysis
Seyed Omid Sadjadi, Jason Pelecanos, Sriram Ganapathy
We present the recent advances along with an error analysis of the IBM speaker recognition system for conversational speech. Some of the key advancements that contribute to our sys…