Not All Fallbacks Are Failures: Understanding and Recovering from Fallbacks in Mobile Voice Assistants

arXiv:2608.30738 · cs.CL · Submitted 2026-08-31 · Read on arXiv

cs.CL

Submitted: 2026-08-31

Updated: 2026-08-31

Comments: Accepted to EMNLP 2026

Code: https://github.com/philotron/VoxFallbacks

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Accuracy — 10× in this paper · explained in 1 episode
Core — 5× in this paper · explained in 2 episodes
Generative Model — 5× in this paper · explained in 2 episodes
Generative Models — 5× in this paper · explained in 2 episodes
F1 Score — 4× in this paper · explained in 3 episodes
AUC — 3× in this paper · explained in 2 episodes
Embeddings — 3× in this paper · explained in 2 episodes
Annotator Agreement — 2× in this paper · explained in 1 episode
Benchmark — 2× in this paper · explained in 2 episodes
Failure Modes — 2× in this paper · explained in 3 episodes
Robustness — 2× in this paper · explained in 5 episodes
Clustering — 1× in this paper · explained in 2 episodes
Consistency — 1× in this paper · explained in 3 episodes
Decoupling — 1× in this paper · explained in 2 episodes
Distillation — 1× in this paper · explained in 2 episodes
Dual Intent and Entity Transformer — 1× in this paper
Frustration — 1× in this paper · explained in 2 episodes
Grounding — 1× in this paper · explained in 3 episodes
Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
Transformer — 1× in this paper · explained in 2 episodes

Sources

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