SpeakerLLM unifies speaker profiling, recording-condition understanding, and structured verification reasoning in an audio-LLM via a hierarchical tokenizer and decision traces.
Reshape Dimensions Network for Speaker Recognition
2 Pith papers cite this work, alongside 28 external citations. Polarity classification is still indexing.
2
Pith papers citing it
28
external citations · Crossref
fields
cs.SD 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Post-processing with an encoder-decoder model yields 22% relative EER reduction on normal-vs-whispered trials and 1.88% EER on whispered-vs-whispered, outperforming ReDimNet-B2.
citing papers explorer
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SpeakerLLM: A Speaker-Specialized Audio-LLM for Speaker Understanding and Verification Reasoning
SpeakerLLM unifies speaker profiling, recording-condition understanding, and structured verification reasoning in an audio-LLM via a hierarchical tokenizer and decision traces.
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Enhancing Speaker Verification with Whispered Speech via Post-Processing
Post-processing with an encoder-decoder model yields 22% relative EER reduction on normal-vs-whispered trials and 1.88% EER on whispered-vs-whispered, outperforming ReDimNet-B2.