Open Access

Quantitative Analysis and AI Assessment of Piano Performance Techniques

  
Mar 17, 2025

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Figure 1.

BP neural network recognition model
BP neural network recognition model

Figure 2.

Basic RNN diagram
Basic RNN diagram

Figure 3.

Bidirectional RNN diagram
Bidirectional RNN diagram

Figure 4.

Fingering evaluation based on AI action recognition
Fingering evaluation based on AI action recognition

Figure 5.

Right hand note and fingering frequency distribution
Right hand note and fingering frequency distribution

Figure 6.

Comparison of various fingering scores
Comparison of various fingering scores

Figure 7.

Fingering sequence score trend
Fingering sequence score trend

Transform the evaluation results of fingering

Fingering class Synreferential Extended finger Dactylocontraction Referral Illegal fingering
Score 1 6 4 1 4 -2
Score 2 6 6 3 -2 -3
Score 3 6 4 3 4 -3
Score of 4 6 1 1 4 -3
Score 5 6 4 4 1 -2
Average score 6 3.8 2.4 2.2 -2.6

The result of fingering sequence evaluation

Fingering sequence number Fingering sequence number Total points Scoring average
1 Standard 48 0.96
2 normal 35 0.67
3 Random 9 0.15

Comparison of annotation results of different algorithms

Accuarcy Unrealizable rate Unreasonable rate
Original LSTM 53.56% 25.24% 19.6%
Fault-tolerant LSTM 59.91 % 23.41% 17.2%
Merged-output LSTM 54.45% 24.7% 20.7%
Judgement-LSTM 68.71% 5% 19.2
Bi-LSTM-CRF (Note difference sequence) 57.11% 17.77% 18.1%
BI-LSTM (Note sequence) 69.7% 0% 3.87%

D major scale and frequency correspondence table(Middle register)

The pentatonic scale roll-call Phonetic name Frequency(HZ)
1 Do D 585
2 Re E 651
3 Mi #F 735
5 Sol A 875
6 La B 991
Chromatic scale
4 Fa G 774
7 Si #C 1104
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English