( en | de | ru )

 

Disambiguation of "Dumpala, Sri Harsha"

Author of the publication

copydeleteadd this publication to your clipboard
Musical Speech: A Transformer-based Composition Tool.

, , , , and . NeurIPS (Competition and Demos), volume 133 of Proceedings of Machine Learning Research, page 253-274. PMLR, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Harsha Mahabaleshwar

Harsha Gurulingappa

Harsha Gurulingappa

Harsha Gurulingappa

Sri Mulato

 

Other publications of authors with the same name

Improving ASR Robustness to Perturbed Speech Using Cycle-consistent Generative Adversarial Networks., , , and . ICASSP, page 5726-5730. IEEE, (2019)Learning to Model Prosodic and Spectral Features for Non-parallel Emotive Speech Conversion., and . Canadian AI, Canadian Artificial Intelligence Association, (2021)An Algorithm for Detection of Breath Sounds in Spontaneous Speech with Application to Speaker Recognition., and . SPECOM, volume 10458 of Lecture Notes in Computer Science, page 98-108. Springer, (2017)k-FFNN: A priori knowledge infused Feed-forward Neural Networks., , and . CoRR, (2017)Knowledge-Driven Feed-Forward Neural Network for Audio Affective Content Analysis., , and . AAAI Workshops, volume WS-18 of AAAI Technical Report, page 16-20. AAAI Press, (2018)Sentiment Classification on Erroneous ASR Transcripts: A Multi View Learning Approach., , , and . SLT, page 807-814. IEEE, (2018)On Combining Global and Localized Self-Supervised Models of Speech., , , and . INTERSPEECH, page 3593-3597. ISCA, (2022)Improved speaker recognition system for stressed speech using deep neural networks., and . IJCNN, page 1257-1264. IEEE, (2017)Analysis of laughter and speech-laugh signals using excitation source information., , , and . ICASSP, page 975-979. IEEE, (2014)Estimating Severity of Depression From Acoustic Features and Embeddings of Natural Speech., , , , , and . ICASSP, page 7278-7282. IEEE, (2021)