2025/08/20 by Zijun Huang, Huang, Zijun, Chengdong Liang +5
Computer Science · #Advanced Data Compression Techniques #Audio and Speech Processing (eess.AS) #FOS: Electrical engineering #Speech Recognition and Synthesis #Speech and Audio Processing #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2508.14732
openalex publication_date 2025/08/20 · openalex created_date 2025/10/16 · openalex updated_date 2026/07/28
The presence of non-speech segments in utterances often leads to the performance degradation of speaker verification. Existing systems usually use voice activation detection as a preprocessing step to cut off long silence segments. However, short silence segments, particularly those between speech segments, still remain a problem for speaker verification. To address this issue, in this paper, we propose a simple wave-level data augmentation method, PadAug, which aims to enhance the system's robustness to silence segments. The core idea of PadAug is to concatenate silence segments with speech segments at the waveform level for model training. Due to its simplicity, it can be directly applied to the current state-of-the art architectures. Experimental results demonstrate the effectiveness of the proposed PadAug. For example, applying PadAug to ResNet34 achieves a relative equal error rate reduction of 5.0% on the voxceleb dataset. Moreover, the PadAug based systems are robust to different lengths and proportions of silence segments in the test data.