ML Anthology

MUSIC COLLAB: An IoT and ML Based Solution for Remote Music Collaboration (Student Abstract)

Nishtha Nayar, Divya Lohani
AAAI 2020 pp. 13883-13884
doi:10.1609/AAAI.V34I10.7214 /aaai/2020/nayar2020aaai-music/

Abstract

Communication using mediums like video and audio is essential for a lot of professions. In this paper, interaction with real-time audio transmission is looked upon using the tools in the domains of IoT and machine learning. Two transport layer protocols - TCP and UDP are examined for audio transmission quality. Further, different RNN models are examined for their efficiency in predicting music and being used as a substitute in case of loss of packets during transmission.

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Cite

Text

Nayar and Lohani. "MUSIC COLLAB: An IoT and ML Based Solution for Remote Music Collaboration (Student Abstract)." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I10.7214

Markdown

[Nayar and Lohani. "MUSIC COLLAB: An IoT and ML Based Solution for Remote Music Collaboration (Student Abstract)." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/nayar2020aaai-music/) doi:10.1609/AAAI.V34I10.7214

BibTeX

@inproceedings{nayar2020aaai-music,
  title     = {{MUSIC COLLAB: An IoT and ML Based Solution for Remote Music Collaboration (Student Abstract)}},
  author    = {Nayar, Nishtha and Lohani, Divya},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2020},
  pages     = {13883-13884},
  doi       = {10.1609/AAAI.V34I10.7214},
  url       = {https://mlanthology.org/aaai/2020/nayar2020aaai-music/}
}