SpeakerCard-1M supplies 56.7k evidence-grounded speaker cards, 1.78M captions, and new cross-modal protocols showing audio LMs lag a dual-encoder baseline on attribute-conditioned verification while joint training barely hurts standard EER.
Dawn of the transformer era in speech emotion recognition: closing the valence gap.IEEE Trans- actions on Pattern Analysis and Machine Intelligence, 45(9): 10745–10759
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A hybrid semi-supervised framework fusing Whisper embeddings with acoustic and prosodic features achieves 0.751 Macro-F1 for speaker confidence detection and outperforms baselines including WavLM, HuBERT, and Wav2Vec 2.0.
A staged multimodal fusion model for predicting six continuous emotion intensities from in-the-wild video achieves 0.4722 validation and 0.57 test Pearson correlation in the EMI challenge.
citing papers explorer
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SpeakerCard-1M: An Evidence-Grounded Corpus for In-the-Wild Speaker Verification
SpeakerCard-1M supplies 56.7k evidence-grounded speaker cards, 1.78M captions, and new cross-modal protocols showing audio LMs lag a dual-encoder baseline on attribute-conditioned verification while joint training barely hurts standard EER.
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A Semi-Supervised Framework for Speech Confidence Detection using Whisper
A hybrid semi-supervised framework fusing Whisper embeddings with acoustic and prosodic features achieves 0.751 Macro-F1 for speaker confidence detection and outperforms baselines including WavLM, HuBERT, and Wav2Vec 2.0.
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Two-Stage Multimodal Framework for Emotion Mimicry Intensity Prediction
A staged multimodal fusion model for predicting six continuous emotion intensities from in-the-wild video achieves 0.4722 validation and 0.57 test Pearson correlation in the EMI challenge.