arXiv (OAI Expanded)
open access
Attacking UTMOS: Probing the Robustness of a Speech Quality Assessment Model
UTMOS has become one of the most commonly used deep neural network-based speech quality assessment (SQA) metrics in speech processing research. In this paper, we attack UTMOS to probe its robustness. Starting from high-quality speech samples, we optimize the input in two directions: a score-preservi
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 Temporal-Envelope Frontend with Learnable Per-Channel Energy Normalization for Whisper-Based Children's ASR#1063148
- SPEAR-Gen: Generation-Aware Pre-training for Unified Speech Representations#1119220
- Automating Speech Audiometry in Quiet and in Noise Using a Deep Neural Network#468216
- Preliminaries to speech analysis#207127
- SITA: Learning Speaker-Invariant and Tone-Aware Speech Representations for Low-Resource Tonal Languages#1110161
Record · ID 1123149
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