MASV: Speaker Verification with Global and Local Context Mamba

Understand

Deep learning models like Convolutional Neural Networks and transformers have shown impressive capabilities in speech verification, gaining considerable attention in the research community.

• However, CNN-based approaches struggle with modeling long-sequence audio effectively, resulting in suboptimal verification performance.
• On the other hand, transformer-based methods are often hindered by high computational demands, limiting their practicality.
• This paper presents the MASV model, a novel architecture that integrates the Mamba module into the ECAPA-TDNN framework.