Speech Lab
Books
Manjunath K E, “Multilingual Phone Recognition in Indian Languages”, Springer Briefs in Speech Technology, 2021, eBook ISBN 978-3-030-80741-2, doi: 10.1007/978-3-030-80741-2
Journals
Manjunath K E, K. M. S. Raghavan, K. S. Rao, D. B. Jayagopi, and V. Ramasubramanian, “Approaches for Multilingual Phone Recognition in Code-Switched and Non-Code-Switched Scenarios using Indian Languages,” ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 20(4), pp. 1-19, 2021. doi: 10.1145/3437256
Manjunath K E, D. B. Jayagopi, K. S. Rao, and V. Ramasubramanian, “Articulatory Feature based Methods for Performance Improvement of Multilingual Phone Recognition Systems using Indian Languages,” Sadhana (Springer), Vol. 45(1), 2020. doi: 10.1007/s12046-020-01428-9
Manjunath K E, D. B. Jayagopi, K. S. Rao, and V. Ramasubramanian, “Development and analysis of multilingual phone recognition systems using Indian languages,” International Journal of Speech Technology, (Springer), pp. 1-12, 2019. doi: 10.1007/s10772-018-09589-z
Conferences
Vandana M. Ladwani and V. Ramasubramanian, “M-ary Hopfield neural network for storage and retrieval of variable length sequences: Multi-limit cycle approach”, accepted in IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR HUMAN-LIKE INTELLIGENCE (IEEE CIHLI) 2022, Singapore,4-7, December 2022.
Vikram. R. Lakkavalli, "AbS for ASR: A New Computational Perspective", IEEE International Conference on Signal Processing and Communications (SPCOM), Bangalore, India, 2022, doi: 10.1109/SPCOM55316.2022.9840830.
Dhanya Eledath, Narasimha Rao Thurlapati, V Pavithra, Tirthankar Banerjee and and V. Ramasubramanian, “Few-shot learning for end-to-end speech recognition: architectural variants for support set generation and optimization,” In EUSIPCO 2022, Serbia, Belgrade, Aug 2022.
Vandana M. Ladwani, and V. Ramasubramanian, “M-ary Hopfield Neural Network Based Associative Memory Formulation: Limit-Cycle Based Sequence Storage and Retrieval”, In Proceedings of ICANN-2021, 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14–17, 2021
Vandana M. Ladwani and V. Ramasubramanian, “Harnessing Energy of M-ary Hopfield Neural Network for Connectionist Temporal Sequence Decoding”, In Proceedings of MIKE 2021, Hammamet, Tunisia, 1-3, November 2021 [2nd Best paper award].
Dhanya Eledath, V Pavithra, Narasimha Rao Thurlapati, Tirthankar Banerjee, and V Ramasubramanian, “Few-shot learning for cross-lingual end-to-end speech recognition,” in Workshop on Machine Learning in Speech and Language Processing 2021 (MLSLP 2021), Satellite Workshop of Interspeech 2021, Brno, Czech Republic, Sep 2021.
Dhanya Eledath, P. Inbarajan, Anurag Biradar, Sathwick Mahadeva and V. Ramasubramanian, “End-to-end speech recognition from raw speech: Multi time-frequency resolution CNN architecture for efficient representation learning,” in 2021 29th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, Aug 2021.
Tirthankar Banerjee, Narasimha Rao Thurlapati, V Pavithra, S Mahalakshmi, Dhanya Eledath, and V Ramasubramanian, “Few-shot learning for frame-wise phoneme recognition: Adaptation of matching networks”, In 29th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, pages 516-520, August 2021. doi:https://doi.org/10.23919/eusipco54536.2021.9616234.
Tirthankar Banerjee, Dhanya Eledath, and V Ramasubramanian, “Few shot learning for cross-lingual isolated word recognition”, In The First International Conference on AI-ML-Systems, Bangalore, India, September 2021. doi:https://doi.org/10.1145/3486001.3486235.
Abhijith Madan, Ayush Khopkar, Shreekantha Nadig, K. M. Srinivasa Raghavan, Dhanya Eledath, and V. Ramasubramanian, “Semi-supervised learning for acoustic model retraining: Handling speech data with noisy transcript,” in 2020 International Conference on Signal Processing and Communications (SPCOM), Bangalore, India, July 2020.
Shreekantha Nadig, V. Ramasubramanian, Sachit Rao, “Multi-target hybrid CTC-Attentional Decoder for joint phoneme-grapheme recognition”, International Conference on Signal Processing and Communications (SPCOM), Bangalore, India, 2020.
Shreekantha Nadig, Sumit Chakraborty, Anuj Shah, Chaitanay Sharma, V. Ramasubramanian, Sachit Rao, ”Jointly learning to align and transcribe using attention-based alignment and uncertainty-to-weigh losses”, International Conferenceon Signal Processing and Communications (SPCOM), Bangalore, India, 2020 (Best Student Paper Award – Honorable Mention).
K. M. Srinivasa Raghavan, S. Kumar, “Hybrid Unsupervised and Supervised Multitask Learning For Speech Recognition in Low Resource Languages”, Workshop on Machine Learning in Speech and Language Processing 2021 (MLSLP-2021), Satellite Workshop of Interspeech-2021, Brno, Czechia, Sep. 2021 (https://homepages.inf.ed.ac.uk/htang2/sigml/mlslp2021/MLSLP2021_paper_8.pdf)
Manjunath K E, K. M. S. Raghavan, K. S. Rao, D. B. Jayagopi, and V. Ramasubramanian, “Multilingual Phone Recognition: Comparison of Traditional versus Common Multilingual Phone-set Approaches and Applications in Code-Switching,” International Symposium on Signal Processing and Intelligent Recognition Systems, Dec. 2019. doi:10.1007/978-981-15-4828-4 7
Rachna Shriwas, Prasun Joshi, Vandana M. Ladwani, and V. Ramasubramanian, “Multi-modal associative storage and retrieval using Hopfield auto-associative memory network”, In Proceedings of ICANN-2019, 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019.
Manjunath K E, K. S. Rao, D. B. Jayagopi, and V. Ramasubramanian, “Indian languages ASR: A multilingual phone recognition framework with IPA based common phone-set, predicted articulatory features and feature fusion,” INTERSPEECH, Sept. 2018, pp. 1016-1020. doi: 10.21437/Interspeech.2018-2529
Manjunath K E, “Study of Multilingual Phone Recognition using Indian Languages,” 4th Doctoral Consortium at INTERSPEECH, 2018.
M. Chellapriyadharshini, A. Toffy, K. M. Srinivasa Raghavan, V. Ramasubramanian, "Semi-supervised and Active-learning Scenarios: Efficient Acoustic Model Refinement for a Low Resource Indian Language" Interspeech 2018, 19th Annual Conference of the International Speech Communication Association, Hyderabad, India, 2-6 Sep. 2018, pp. 1041-1045, doi: https://doi.org/10.21437/Interspeech.2018-2486
Manjunath K E, K. S. Rao and D. B. Jayagopi, ”Development of multilingual phone recognition system for Indian languages,” IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), Aug. 2017, pp. 1-6. doi: 10.1109/SPICES.2017.8091271
Vandana M. Ladwani, Y. Vaishnavi, R. Shreyas, B.R. Vinay Kumar, N. Harisha, S. Yogesh, P. Shivaganga, V. Ramasubramanian, “Hopfield net framework for audio search”, In Proceedings of NCC-2017, IIT-Madras, Chennai, India, 2017.
Vandana M. Ladwani, Y. Vaishnavi, and V. Ramasubramanian, “Hopfield auto-associative memory network for content-based text-retrieval”, In Proceedings of ICANN-2017, 26th International Conference on Artificial Neural Networks, Alghero, Italy, Sep 2017
Y. Vaishnavi, R. Shreyas, S. Suhas, U. N. Surya, V. M. Ladwani, and V. Ramasubramanian, “Associative memory framework for speech recognition: Adaptation of Hopfield network”, In Proceedings of INDICON-2016, IEEE Annual India Conference, pages 1-6, 2016.