Title: Interactive piano automatic accompaniment intelligent system based on machine learning model

Authors: Wei You

Addresses: Conservatory of Music and Dance, Jingdezhen University, Jiangxi, 333000, China

Abstract: In order to enrich the expression of piano melodies, the article applies the IBi-LSTM algorithm for the automatic arrangement of piano harmonies by constructing a network scoring platform for users to audition and score. The results show that the IBi-LSTM algorithm performs better and has less perplexity than algorithms such as LSTM. Compared with other methods, the multi-basic frequency estimation method used is more effective, with a higher recall of 84.42% and a higher F-value of 81.38% under the MUS subset. In the harmonic arrangement effect, most of the auditioners rated higher than 4, with an average rating of 3.99 and a maximum rating of 4.6. The article uses the method to achieve automatic piano accompaniment and is well received by the auditioners.

Keywords: Bi-LSTM; machine learning; interactive; piano; accompaniment; harmonic arrangement.

DOI: 10.1504/IJCSYSE.2025.149217

International Journal of Computational Systems Engineering, 2025 Vol.9 No.2/3/4, pp.204 - 213

Received: 10 Apr 2023
Accepted: 20 Aug 2023
Published online: 20 Oct 2025 *

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