Pitch estimation is to estimate the fundamental frequency and the midi number and plays a critical role in music signal analysis and vocal signal processing. In this work, we proposed a new architecture based on a learning-based enhancement preprocessor and a combination of several traditional and deep learning pitch estimation methods to achieve better pitch estimation performance in both noisy and clean scenarios. We test 17 different types of noise and 4 SNRdb noise levels. The results show that the proposed pitch estimation can perform better in both noisy and clean scenarios with short response time.

翻译：音高估计旨在估算基频及MIDI编号，在音乐信号分析与语音信号处理中具有关键作用。本研究提出一种基于学习型增强预处理器的全新架构，通过融合多种传统与深度学习音高估计方法，旨在在噪声与干净场景下均实现更优的音高估计性能。我们测试了17种不同类型噪声与4种信噪比（SNRdb）噪声水平。结果表明，所提出的音高估计算法在噪声与干净场景中均能以较短响应时间取得更优表现。