Joint-marginal alignment plus adaptive weighting in speech VAE distillation yields the best combined performance on reconstruction, understanding, and generation tasks.
HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,
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Lightweight training strategies allow speech-aware LLMs to output accurate word timestamps alongside ASR transcripts while also improving recognition quality across datasets.
citing papers explorer
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On the Distillation Loss Functions of Speech VAE for Unified Reconstruction, Understanding, and Generation
Joint-marginal alignment plus adaptive weighting in speech VAE distillation yields the best combined performance on reconstruction, understanding, and generation tasks.
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In-Sync: Adaptation of Speech Aware Large Language Models for ASR with Word Level Timestamp Predictions
Lightweight training strategies allow speech-aware LLMs to output accurate word timestamps alongside ASR transcripts while also improving recognition quality across datasets.