2 citations · 6 across the 5 of their papers we have counts for
6 papers
Towards Probing Contact Center Large Language Models
Varun Nathan, Ayush Kumar, Digvijay Ingle +1
Fine-tuning large language models (LLMs) with domain-specific instructions has emerged as an effective method to enhance their domain-specific understanding. Yet, there is limited…
Low Resource Pipeline for Spoken Language Understanding via Weak Supervision
Ayush Kumar, Rishabh Kumar Tripathi, Jithendra Vepa
In Weak Supervised Learning (WSL), a model is trained over noisy labels obtained from semantic rules and task-specific pre-trained models. Rules offer limited generalization over t…
Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent Detection
Ayush Kumar, Vijit Malik, Jithendra Vepa
Intent Detection is one of the core tasks of dialog systems. Few-shot Intent Detection is challenging due to limited number of annotated utterances for novel classes. Generalized F…
What BERT Based Language Models Learn in Spoken Transcripts: An Empirical Study
Ayush Kumar, Mukuntha Narayanan Sundararaman, Jithendra Vepa
Language Models (LMs) have been ubiquitously leveraged in various tasks including spoken language understanding (SLU). Spoken language requires careful understanding of speaker int…
Phoneme-BERT: Joint Language Modelling of Phoneme Sequence and ASR Transcript
Mukuntha Narayanan Sundararaman, Ayush Kumar, Jithendra Vepa
Recent years have witnessed significant improvement in ASR systems to recognize spoken utterances. However, it is still a challenging task for noisy and out-of-domain data, where s…
Gated Mechanism for Attention Based Multimodal Sentiment Analysis
Ayush Kumar, Jithendra Vepa
Multimodal sentiment analysis has recently gained popularity because of its relevance to social media posts, customer service calls and video blogs. In this paper, we address three…