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The Machines Are Calling: Measuring Automated and Synthetic Voices in Unwanted Inbound Calls — arXiv:2609.11137

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.11137
License (as archived): CC0-1.0
Archived: 2026-10-16T05:45:06.341Z
SHA-256 of the archived text: 1d7440b5e70939b7c0d2122251b26527ac2d1c10a21200be3a588de59e476586
Stable URL of this page: https://metraipolis.com/documento/dc_c23a67eb385a

How to cite

The Machines Are Calling: Measuring Automated and Synthetic Voices in Unwanted Inbound Calls — arXiv:2609.11137 — arXiv (en), https://arxiv.org/abs/2609.11137 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_c23a67eb385a (Metraipolis archive dc_c23a67eb385a, sha256 1d7440b5e70939b7c0d2122251b26527ac2d1c10a21200be3a588de59e476586)

BibTeX

@misc{dcc23a67eb385a,
  title = {The Machines Are Calling: Measuring Automated and Synthetic Voices in Unwanted Inbound Calls — arXiv:2609.11137},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.11137},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_c23a67eb385a; sha256 1d7440b5e70939b7c0d2122251b26527ac2d1c10a21200be3a588de59e476586},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.11137. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

In February 2024 the U.S. Federal Communications Commission (FCC) placed AI-generated voices under the Telephone Consumer Protection Act (TCPA). Yet no peer-reviewed measurement says how much unwanted call traffic is placed by a machine, or how much of that machine speech is synthesized rather than played from a recording. We report both with a disclosed pipeline. An interactive voice honeypot (language-model personas on real U.S. numbers, the caller recorded on its own track) recorded 10,987 calls over 66 days. Three instruments read each opening: an audio fingerprint that finds the same recording played on other calls, a commercial synthetic-speech detector on the caller's first ten seconds, and blinded listeners who check what it flags. Of the 7,233 greeted calls we analyze, 13.8% open with a recording we also heard on another call, and 13.1% with fresh audio the detector labels synthetic. A further 9.9% open with a caller who never spoke after our greeting, 54.2% with fresh audio the detector labels human, and 9.0% could not be scored. Machine-voiced openings are therefore at least 26.9%, a further tenth of calls are silent connections we read as machine-placed, and replays of a recording make up 45% of the detector's own rate (29.3% of 6,192 scored openings). The same waveform played on two calls lands on opposite sides of the detector's threshold 13.6% of the time, and eleven listeners confirm 54.4% of what it flags. Synthetic openings concentrate in lead-generation spam (33.8%), not fraud (21.1%); 0.44% disclose automation. Prevalence tracks how long a bait number has circulated (59% against 19% in the same weeks): seeding history, not calendar time, explains the trend. Campaigns outlast their numbers: one recorded compliance notice opens calls in six campaigns, and one synthetic voice serves nine.

Tema degli esploratori: governance digitale e beni comuni (retro-catalogo arXiv: annunci del 2026-09-11 in cs.CY).
Categorie arXiv: Cryptography and Security (cs.CR) ; Computers and Society (cs.CY); Sound (cs.SD).
Pagina del lavoro: https://arxiv.org/abs/2609.11137 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-16T05:29:23.835Z dalla pagina https://arxiv.org/catchup/cs.CY/2026-09-11?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).