Title: Influence of Clean Speech Characteristics on Speech Enhancement Performance Show Chinese title

Title: 清洁语音特征对语音增强性能的影响

Abstract: Speech enhancement (SE) performance is known to depend on noise characteristics and signal to noise ratio (SNR), yet intrinsic properties of the clean speech signal itself remain an underexplored factor. In this work, we systematically analyze how clean speech characteristics influence enhancement difficulty across multiple state of the art SE models, languages, and noise conditions. We extract a set of pitch, formant, loudness, and spectral flux features from clean speech and compute correlations with objective SE metrics, including frequency weighted segmental SNR and PESQ. Our results show that formant amplitudes are consistently predictive of SE performance, with higher and more stable formants leading to larger enhancement gains. We further demonstrate that performance varies substantially even within a single speaker's utterances, highlighting the importance of intraspeaker acoustic variability. These findings provide new insights into SE challenges, suggesting that intrinsic speech characteristics should be considered when designing datasets, evaluation protocols, and enhancement models. Show Chinese abstract

Abstract: 语音增强（SE）性能已知取决于噪声特征和信噪比（SNR），但干净语音信号本身的内在特性仍然是一个研究不足的因素。 在本工作中，我们系统地分析了干净语音特征如何影响多种最先进的SE模型、语言和噪声条件下的增强难度。 我们从干净语音中提取一组基频、共振峰、响度和频谱通量特征，并计算与客观SE指标的相关性，包括频率加权分段SNR和PESQ。 我们的结果表明，共振峰幅度始终能预测SE性能，较高的且更稳定的共振峰会导致更大的增强收益。 我们进一步证明，即使在同一说话人的发音中，性能也会有很大差异，这突显了说话人内部声学变异的重要性。 这些发现为SE挑战提供了新的见解，表明在设计数据集、评估协议和增强模型时应考虑内在语音特征。