arXiv (All)
open access
Inference-Time Target Speaker Unlearning in LLM-Based Automatic Speech Recognition
We introduce target-speaker unlearning ASR (TSU-ASR) task in a fully end-to-end framework for multi-speaker ASR and diarization. Given a multi-speaker utterance and a set of opt-out speakers who do not wish to have their speech transcribed, the task requires an ASR system to transcribe all speakers
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
- Asymmetric Classifier-Free Guidance for Target-Speaker ASR#1104675
- Voices as Handles: Reasoning about Speaker Identity with Frozen Text LLMs#1143102
- Pushing the Boundaries of Streaming Multi-Speaker ASR: A Systematic Study of Architectural Trade-offs#997163
- X2Streaming-ASR: wait when uncertain, emit when ready for streaming ASR#1123217
- Downstream-Task-Aware Unified Source Separation#998649
Record · ID 1104638
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