Srinivasa Raghavan K. M.

According to our database1, Srinivasa Raghavan K. M. authored at least 12 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2025
RESPIN-S1.0: A read speech corpus of 10000+ hours in dialects of nine Indian Languages.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024
Adapter pre-training for improved speech recognition in unseen domains using low resource adapter tuning of self-supervised models.
Proceedings of the 25th Annual Conference of the International Speech Communication Association, 2024

2023
Model Adaptation for ASR in low-resource Indian Languages.
CoRR, 2023


Gated Multi Encoders and Multitask Objectives for Dialectal Speech Recognition in Indian Languages.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2021
Approaches for Multilingual Phone Recognition in Code-switched and Non-code-switched Scenarios Using Indian Languages.
ACM Trans. Asian Low Resour. Lang. Inf. Process., 2021

Multilingual and code-switching ASR challenges for low resource Indian languages.
CoRR, 2021

MUCS 2021: Multilingual and Code-Switching ASR Challenges for Low Resource Indian Languages.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

2020
Semi-supervised learning for acoustic model retraining: Handling speech data with noisy transcript.
Proceedings of the International Conference on Signal Processing and Communications, 2020

2018
Semi-supervised and Active-learning Scenarios: Efficient Acoustic Model Refinement for a Low Resource Indian Language.
Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

2017
A comparative study on the effect of different codecs on speech recognition accuracy using various acoustic modeling techniques.
Proceedings of the Twenty-third National Conference on Communications, 2017

Phoneme State Posteriorgram Features for Speech Based Automatic Classification of Speakers in Cold and Healthy Condition.
Proceedings of the 18th Annual Conference of the International Speech Communication Association, 2017


  Loading...