Abstract
The Frequency Following Response (FFR) reflects the brain's neural encoding of auditory stimuli including speech. Because the fundamental frequency (F0), a physical correlate of pitch, is one of the essential features of speech, there has been particular interest in characterizing the FFR at F0, especially when F0 varies over time. The standard method for extracting F0 in FFRs has been the Autocorrelation Function (ACF). This paper investigates harmonic-structure-based F0 estimation algorithms, originally developed for speech and music, and resolves their poor performance when applied to FFRs in two steps. Firstly, given that unlike in speech or music, stimulus F0 of FFRs is already known, we introduce a stimulus-aware filterbank that selectively aggregates amplitudes at F0 and its harmonics while suppressing noise at non-harmonic frequencies. This method, called Harmonic Amplitude Summation (HAS), evaluates F0 candidates only within a range centered around the stimulus F0. Secondly, unlike other pitch tracking methods that select the highest peak, our method chooses the most prominent one, as it better reflects the underlying periodicity of FFRs. To the best of our knowledge, this is the first study to propose an F0 estimation algorithm for FFRs that relies on harmonic structure. Analyzing recorded FFRs from 16 normal hearing subjects to 4 natural speech stimuli with a wide F0 variation from 89 Hz to 452 Hz showed that this method outperformed ACF by reducing the average Root-Mean-Square-Error (RMSE) within each response and stimulus F0 contour pair by 8.8% to 47.4%, depending on the stimulus.
Abstract (translated)
频率跟随响应（FFR）反映了大脑对包括语音在内的听觉刺激的神经编码。由于基频（F0），即音高的物理对应物，是语音的基本特征之一，因此在研究FFR中的F0特性时，尤其是在F0随时间变化的情况下，人们对此特别感兴趣。传统上，自相关函数（ACF）被用作从FFR中提取F0的标准方法。本文探讨了基于谐波结构的F0估计算法，这些算法最初是为了语音和音乐开发的，并通过两个步骤解决了当应用于FFRs时性能不佳的问题。 首先，考虑到与语音或音乐不同，在FFRs中的刺激F0是已知的，我们引入了一种了解刺激的滤波器组。这种名为谐振幅叠加（HAS）的方法选择性地在F0及其谐音频率处聚合幅度，并抑制非谐音频率的噪声。这种方法仅在一个围绕刺激F0为中心的范围内评估F0候选值。 其次，不同于其他音高追踪方法会选择最高峰，我们的方法选择了最显著的一个峰值，因为这更好地反映了FFRs中的周期性特征。据我们所知，这是首次提出依赖于谐波结构来估计FFR中基频（F0）的方法的研究。 通过对16名正常听力受试者对4种自然语音刺激（其基频范围从89Hz到452Hz）的记录进行分析，结果显示该方法在减少每个响应和刺激F0轮廓对之间的平均均方根误差（RMSE）方面优于ACF方法。具体而言，根据不同的刺激类型，这种新方法将RMSE减少了8.8%至47.4%不等。
URL
https://arxiv.org/abs/2506.19253
