Transfer learning has been shown to be effective in enhancing speaker verification performance in low-resource conditions. However, the inclusion of additional datasets may cause domain mismatch. Additionally, mismatched data volume and model complexity during fine-tuning can degrade speaker verification performance. In this paper, we propose a domain-weighted allocation fine-tuning strategy that employs the Kernel Mean Matching (KMM) algorithm to adjust the distribution differences between the in-domain and out-of-domain datasets. It assigns weights to each sample in the source datasets and utilizes the maximum mean discrepancy (MMD) distance to measure the effectiveness of distribution adaptation. The domain-weighted allocation fine-tuning strategy (DWA-FT) effectively mitigates the issue of domain mismatch during model training. We also propose two backend canonical correlation analysis (CCA) embedding transformation methods, the CCA embedding fusion and the CCA embedding constraint. These methods aim to enhance the quality of speaker embeddings. The experimental results demonstrate that the proposed methods effectively enhance the performance of the speaker verification system in low-resource scenarios. Compared to the baseline, our methods achieve relative improvements of 51.03% in PLDA scoring and 46.02% in cosine similarity scoring on the Himia dataset.

Han Wang

Mingrui He

Mingjun Zhang

Changzhi Luo

Longting Xu

EURASIP Journal on Audio Speech and Music Processing

“EURASIP JOURNAL ON AUDIO, SPEECH, AND MUSIC PROCESSING”旨在汇集致力于各种音频信号处理理论和应用的研究人员、科学家和工程师，特别关注语音和音乐。 EURASIP 音频、语音和音乐处理期刊将是一本跨学科期刊，用于传播语音通信和音频处理的所有基本和应用方面。

The "Eurasip Journal on Audio, Speech, and Music Processing" aims to bring together researchers, scientists, and engineers dedicated to the theory and application of various audio signal processing, with a particular focus on speech and music. This journal will serve as an interdisciplinary platform for disseminating all fundamental and applied aspects of speech communication and audio processing.

《Eurasip Journal on Audio, Speech, and Music Processing》旨在汇聚致力于音频信号处理理论与应用的研究人员、科学家和工程师，特别关注语音和音乐领域。该期刊将作为一个跨学科的平台，传播语音通信和音频处理的基本理论及其应用。

Category	Quartile
计算机科学	3
计算机科学, 声学	3
计算机科学, 工程电子与电气	3

Domain-weighted transfer learning and discriminative embeddings for low-resource speaker verification

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Journal Info

Category	Quartile
ENGINEERING, ELECTRICAL & ELECTRONIC	3