arXiv (All)
open access
An Investigation of Reprogramming for Cross-Language Adaptation in Speaker Verification Systems
Language mismatch is among the most common and challenging domain mismatches in deploying speaker verification (SV) systems. Adversarial reprogramming has shown promising results in cross-language adaptation for SV. The reprogramming is implemented by padding learnable parameters on the two sides of
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- A Unified Uncertainty-Aware Back-End for Speaker Verification: Scoring, Normalization, and Calibration#1083186
- Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition#133948
- MLAAD: The Multi-Language Audio Anti-Spoofing Dataset#785033
- MLAAD: The Multi-Language Audio Anti-Spoofing Dataset#783443
- Collapse, Not Invariance: Diagnosing Auxiliary Objectives in Speech Anti-Spoofing#1155474
Record · ID 972885
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive