IJEBM | Applications of AI and NLP to advance Music Recommendations on Voice Assistants

Indexing and Abstracting

Applications of AI and NLP to advance Music Recommendations on Voice Assistants

Ashlesha V Kadam

International Journal of Engineering, Business And Management(IJEBM), Vol-7,Issue-3, May - June 2023, Pages 55-57 , 10.22161/ijebm.7.3.9

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Article Info: Received: 30 Apr 2023; Received in revised form: 26 May 2023; Accepted: 03 Jun 2023; Available online: 10 Jun 2023

Abstract:

This paper builds on the popular use case of music requests on voice assistants like Siri, Google Assistant, Alexa, and others and explores the different AI and NLP techniques. The paper particularly focuses on how each of these techniques can be applied in the context of musical recommendations and experiences on voice assistants. It enumerates specific problems in the space of music recommendations and illustrates how specific techniques like multi-armed bandits can be applied.

Keywords:

applications of AI, music, recommendations, voice assistants, voice technology.

References:

[1] Yandre M.G. Costa, Luiz S. Oliveira, Carlos N. Silla, “An evaluation of Convolutional Neural Networks for music classification using spectrograms” Applied Soft Computing, Volume 52, 2017, Pages 28-38
[2] Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart “Online Bayesian Transfer Learning for Sequential Data Modeling”, Published as a conference paper at ICLR 2017
[3] Mayank Kejriwal, “Knowledge Graphs: A Practical Review of the Research Landscape”, Special Issue Knowledge Graph Technology and Its Applications
[4] Chunqiu Zeng, Qing Wang, Shekoofeh Mokhtari, Tao Li, “Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit”