337 citations · 470 across the 50 of their papers we have counts for
12 papers · 1 filter
AMPS: ASR with Multimodal Paraphrase Supervision
Abhishek Gupta, Amruta Parulekar, Sameep Chattopadhyay +1
Spontaneous or conversational multilingual speech presents many challenges for state-of-the-art automatic speech recognition (ASR) systems. In this work, we present a new technique…
Parameter-efficient Adaptation of Multilingual Multimodal Models for Low-resource ASR
Abhishek Gupta, Amruta Parulekar, Sameep Chattopadhyay +1
Automatic speech recognition (ASR) for low-resource languages remains a challenge due to the scarcity of labeled training data. Parameter-efficient fine-tuning and text-only adapta…
SALSA: Speedy ASR-LLM Synchronous Aggregation
Ashish Mittal, Darshan Prabhu, Sunita Sarawagi +1
Harnessing pre-trained LLMs to improve ASR systems, particularly for low-resource languages, is now an emerging area of research. Existing methods range from using LLMs for ASR err…
Multi-Convformer: Extending Conformer with Multiple Convolution Kernels
Darshan Prabhu, Yifan Peng, Preethi Jyothi +1
Convolutions have become essential in state-of-the-art end-to-end Automatic Speech Recognition~(ASR) systems due to their efficient modelling of local context. Notably, its use in…
LoFTI: Localization and Factuality Transfer to Indian Locales
Sona Elza Simon, Soumen Kumar Mondal, Abhishek Singhania +2
Large language models (LLMs) encode vast amounts of world knowledge acquired via training on large web-scale datasets crawled from the internet. However, these datasets typically e…
Boosting Zero-Shot Crosslingual Performance using LLM-Based Augmentations with Effective Data Selection
Barah Fazili, Ashish Sunil Agrawal, Preethi Jyothi
Large language models (LLMs) are very proficient text generators. We leverage this capability of LLMs to generate task-specific data via zero-shot prompting and promote cross-lingu…