pith:JYNIXK3X
On the Distillation Loss Functions of Speech VAE for Unified Reconstruction, Understanding, and Generation
Joint-marginal alignment with adaptive weighting delivers the best overall performance in speech VAEs for reconstruction, understanding, and generation.
arxiv:2604.12383 v2 · 2026-04-14 · cs.SD
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Claims
Extensive experiments show that the joint-marginal alignment approach with adaptive weighting can achieve the best overall performance while allowing for a controllable balance.
That the chosen SSL features and evaluation metrics adequately represent the full space of reconstruction, understanding, and generation needs without hidden task-specific biases.
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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Receipt and verification
| First computed | 2026-05-26T02:04:10.691278Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4e1a8bab7784047d5254c1e04682a2cc30ea6419e47b1aab353d80f6b9011107
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JYNIXK3XQQCH2USUYHQENAVCZQ \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 4e1a8bab7784047d5254c1e04682a2cc30ea6419e47b1aab353d80f6b9011107
Canonical record JSON
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