Chinese Traditional Musical Instrument Evaluation Based on a Smart Microphone Array Sensor

Abstract

For Chinese traditional musical instruments, the general subjective evaluation method by experts is not cost-effective and is limited by fewer and fewer experts, but a clear physical law is very hard to established by physicists. Considering the effectiveness of artificial neural networks (ANNs) for complex system, for a Chinese lute case, a neural network based 8-microphone array is applied to correlate the objective instrument acoustic features with expert subjective evaluations in this paper. The acoustic features were recorded by a microphone array sensor and extracted as the constant-Q transform coefficients, Mel-frequency cepstral coefficients and correlation coefficients between each microphone for ANNs input. The acoustic library establishment, acoustic features extractions, and deep learning model for Chinese lutes evaluation are reported in this paper.