Chirp-train Signal Dataset

该数据集包含了一系列通过级联全通滤波器处理后的啁啾信号，这些信号被用于训练模拟低频振荡器（LFO）驱动的音频效果模型。数据集中包含了数字和模拟相位效果中LFO频率和反馈参数的变化，具体的设置在相关论文中有详细阐述。该数据集规模为6.67秒的训练数据，共计使用了12个音频样本。这项任务的目的是训练神经网络模型以模拟音频效果。

This dataset comprises a series of chirp signals processed by cascaded all-pass filters, which are employed to train audio effect models driven by low-frequency oscillators (LFOs). It includes variations of LFO frequency and feedback parameters for both digital and analog phase effects, with specific parameter settings elaborated in the associated academic paper. The dataset totals 6.67 seconds of training audio material, utilizing 12 audio samples in total. The goal of this task is to train neural network models to simulate audio effects.