Does a prosody-trained representation help beyond trainable fusion? A parameter-matched study with frozen HuBERT

arXiv:2609.36754 · eess.AS, cs.CL · Submitted 2026-09-29 · Read on arXiv

eess.AS, cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Comments: Submitted to ICASSP 2027

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

Terminology

• Transformer — 7× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Self-Supervised Learning — 2× in this paper · explained in 7 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Automatic Speech Recognition (ASR) — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning (SSL) — 1× in this paper · explained in 4 episodes

Sources

• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

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