Pith Number

pith:IG5772UI

pith:2026:IG5772UIP6IQ3QCAS2AHWQWHGO

not attested not anchored not stored refs resolved

Voice ''Cloning'' is Style Transfer

Anna Pot, Federico Bianchi, James Zou, Kaitlyn Zhou, Martijn Bartelds, Yongchan Kwon

Voice cloning models apply style transfer to source voices rather than faithfully replicating them.

arxiv:2605.16578 v1 · 2026-05-15 · cs.SD · cs.AI · cs.HC · cs.LG

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{IG5772UIP6IQ3QCAS2AHWQWHGO}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

widely-used voice cloning models systematically apply style transfer to source voices. As rated by human annotators, cloned voices are perceived as more authoritative, warm, customer-service-like, and human-like compared to their sources. Human annotators also report greater trust in cloned voices than source voices, and a greater willingness to disclose sensitive personal information to them. voice cloning leads to homogenization of speaker characteristics, as measured by reduced variance in accent, speaking rate, and the audio embedding space.

C2weakest assumption

The assumption that differences in human ratings and reduced variance are caused by inherent style transfer in the cloning models rather than by specific training data choices, model architectures, or unmeasured confounding factors in the evaluation setup.

C3one line summary

Voice cloning models perform style transfer rather than faithful cloning, producing voices rated as more authoritative and warm with reduced variance in accent and speaking rate.

References

62 extracted · 62 resolved · 0 Pith anchors

[1] Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale , author=. 2023 , eprint= 2023

[2] Advances in Neural Information Processing Systems , primaryClass= 2018

[3] NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models , author=. 2024 , eprint= 2024

[4] NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers , author=. 2023 , eprint= 2023

[5] Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers , author=. 2023 , eprint= 2023

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:02:30.705299Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

41bbffea887f910dc04096807b42c73397c8ef9a43aa60c321615186fd1cd664

Aliases

arxiv: 2605.16578 · arxiv_version: 2605.16578v1 · doi: 10.48550/arxiv.2605.16578 · pith_short_12: IG5772UIP6IQ · pith_short_16: IG5772UIP6IQ3QCA · pith_short_8: IG5772UI

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/IG5772UIP6IQ3QCAS2AHWQWHGO \
  | 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: 41bbffea887f910dc04096807b42c73397c8ef9a43aa60c321615186fd1cd664

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "7994ed9c27f65e8a8a945f8d938883ff7e00683fa643b4e689b7a093a42ceff2",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.HC",
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.SD",
    "submitted_at": "2026-05-15T19:32:28Z",
    "title_canon_sha256": "a516748f6815ebcfd4bc0425f30462ef22fe4b8fe48f25d6e95d145c7c19c8f3"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16578",
    "kind": "arxiv",
    "version": 1
  }
}