Real-Time Pitch Tracking in Audio Signals with the Extended Complex Kalman Filter
Real-Time Pitch Tracking in Audio Signals with the Extended Complex Kalman Filter
复制标题
使用扩展复杂卡尔曼滤波器实时跟踪音频信号
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
C. Chafe
中科院分区：
文献类型：
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作者：
Orchisama Das;J. Smith;C. Chafe
卡尔曼滤波器是广泛用于机器人、导航、语音增强和金融领域的著名工具。本文提出了一种基于扩展复卡尔曼滤波（ECKF）的基音跟踪器。这种音调跟随器的优点在于，它在逐个样本的基础上操作，不像在音调估计中最常用的其他基于块的算法。因此，它估计采样同步基频（假设为感知音调），这使得它非常适合实时实现。同时，ECKF还跟踪输入音频信号的幅度包络。最后，我们测试了我们的ECKF音高检测器上播放的各种装饰，如颤音，滑音和颤音的大提琴和低音提琴录音，并比较其结果与著名的YIN估计，总结我们的算法的有效性。
The Kalman filter is a well-known tool used extensively in robotics, navigation, speech enhancement and finance. In this paper, we propose a novel pitch follower based on the Extended Complex Kalman Filter (ECKF). An advantage of this pitch follower is that it operates on a sample-by-sample basis, unlike other block-based algorithms that are most commonly used in pitch estimation. Thus, it estimates sample-synchronous fundamental frequency (assumed to be the perceived pitch), which makes it ideal for real-time implementation. Simultaneously, the ECKF also tracks the amplitude envelope of the input audio signal. Finally, we test our ECKF pitch detector on a number of cello and double bass recordings played with various ornaments, such as vibrato, portamento and trill, and compare its result with the well-known YIN estimator, to conclude the effectiveness of our algorithm.