5 papers · 1 filter
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…
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-…
Efficient infusion of self-supervised representations in Automatic Speech Recognition
Darshan Prabhu, Sai Ganesh Mirishkar, Pankaj Wasnik
Self-supervised learned (SSL) models such as Wav2vec and HuBERT yield state-of-the-art results on speech-related tasks. Given the effectiveness of such models, it is advantageous t…
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…