Evaluating Machine Unlearning in ASR

arXiv:2609.34092 · cs.CL · Submitted 2026-09-28 · Read on arXiv

cs.CL

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/dmbdpt/asr-unlearning-evalu

Terminology

• Machine Unlearning — 17× in this paper · explained in 2 episodes
• AUC — 9× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Approximate Unlearning — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Catastrophic Forgetting — 2× in this paper · explained in 5 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Area Under the Curve — 1× in this paper
• Automatic Speech Recognition — 1× in this paper
• Automatic Speech Recognition (ASR) — 1× in this paper · explained in 2 episodes
• Connectionist Temporal Classification — 1× in this paper
• Distillation — 1× in this paper · explained in 2 episodes
• Equal Error Rate — 1× in this paper
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Kullback-Leibler (KL) Divergence — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Membership Inference Attacks (MIAs) — 1× in this paper · explained in 2 episodes
• Random Forest — 1× in this paper
• Word Error Rate — 1× in this paper

Sources

• Is your algorithm unlearning or untraining?
• Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition

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