arXiv (OAI Expanded)
open access
Probing Layer-Wise Robustness and Sensitivity of Speech Enhancement Models
Speech enhancement (SE) models advance rapidly, yet how input degradation affects their internal representations remains underexplored. We introduce a probing framework to characterize how internal representations in SE models behave under controlled input degradation. We probe three SE models acros
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
- DualSpecSE: A Dual-Path Speech Enhancement Network Integrating Mel and Complex Spectrograms#1083404
- Coupled Meta-Adaptive Filtering for Active Noise Control Under Time-Varying Acoustic Paths#1105504
- Decoding Order Matters in Autoregressive Speech Synthesis#1049740
- Improving Predicted MOS Scores, Not Perceived Quality: Multi-Predictor Test-Time Optimization of Enhanced Speech#1143995
- Traceable TTS: Toward Watermark-Free TTS with Strong Traceability#925050
Record · ID 1110146
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