Nabarun Goswami

According to our database, Nabarun Goswami authored at least 7 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

HyperVQ: MLR-based Vector Quantization in Hyperbolic Space.

Nabarun Goswami, Yusuke Mukuta, Tatsuya Harada

CoRR, 2024

Advancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation.

Kohei Uehara, Nabarun Goswami, Hanqin Wang, Toshiaki Baba, Kohtaro Tanaka, Tomohiro Hashimoto, Kai Wang, Rei Ito, Takagi Naoya, Ryo Umagami, Yingyi Wen, Tanachai Anakewat, Tatsuya Harada

CoRR, 2024

2023

The Sound Demixing Challenge 2023 - Music Demixing Track.

Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai, Woosung Choi, Marco A. Martínez Ramírez, Wei-Hsiang Liao, Igor Gadelha, Geraldo Ramos, Eddie Hsu, Hugo Rodrigues, Fabian-Robert Stöter, Alexandre Défossez, Yi Luo, Jianwei Yu, Dipam Chakraborty, Sharada P. Mohanty, Roman A. Solovyev, Alexander L. Stempkovskiy, Tatiana Habruseva, Nabarun Goswami, Tatsuya Harada, Minseok Kim, Jun Hyung Lee, Yuanliang Dong, Xinran Zhang, Jiafeng Liu, Yuki Mitsufuji

CoRR, 2023

2022

SATTS: Speaker Attractor Text to Speech, Learning to Speak by Learning to Separate.

Nabarun Goswami, Tatsuya Harada

Proceedings of the Interspeech 2022, 2022

2019

Recursive Speech Separation for Unknown Number of Speakers.

Naoya Takahashi, Sudarsanam Parthasaarathy, Nabarun Goswami, Yuki Mitsufuji

Proceedings of the Interspeech 2019, 2019

2018

Mmdenselstm: An Efficient Combination of Convolutional and Recurrent Neural Networks for Audio Source Separation.

Naoya Takahashi, Nabarun Goswami, Yuki Mitsufuji

Proceedings of the 16th International Workshop on Acoustic Signal Enhancement, 2018

PhaseNet: Discretized Phase Modeling with Deep Neural Networks for Audio Source Separation.

Naoya Takahashi, Purvi Agrawal, Nabarun Goswami, Yuki Mitsufuji

Proceedings of the Interspeech 2018, 2018