VoiceBench is the first benchmark for multi-faceted evaluation of LLM voice assistants using real and synthetic spoken instructions with speaker, environmental, and content variations.
Distilling an end-to-end voice as- sistant without instruction training data
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Gaslighting attacks using Anger, Cognitive Disruption, Sarcasm, Implicit, and Professional Negation strategies cause a 24.3% average accuracy drop in Speech LLMs while also triggering behavioral changes like apologies and refusals.
A literature survey that organizes spoken language models by architecture, training, and evaluation choices and identifies key challenges and future directions.
citing papers explorer
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VoiceBench: Benchmarking LLM-Based Voice Assistants
VoiceBench is the first benchmark for multi-faceted evaluation of LLM voice assistants using real and synthetic spoken instructions with speaker, environmental, and content variations.
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Benchmarking Gaslighting Attacks Against Speech Large Language Models
Gaslighting attacks using Anger, Cognitive Disruption, Sarcasm, Implicit, and Professional Negation strategies cause a 24.3% average accuracy drop in Speech LLMs while also triggering behavioral changes like apologies and refusals.
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On The Landscape of Spoken Language Models: A Comprehensive Survey
A literature survey that organizes spoken language models by architecture, training, and evaluation choices and identifies key challenges and future directions.