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# VoxKnesset: A Large-Scale Longitudinal Hebrew Speech Dataset for Aging Speaker Modeling

**Authors:** Yanir Marmor; Arad Zulti; David Krongauz; Adam Gabet; Yoad Snapir; Yair Lifshitz; Eran Segal · **Year:** 2026 · **Venue:** arXiv:2603.01270 **Link:** [arxiv.org/abs/2603.01270](https://arxiv.org/abs/2603.01270) · library `langstream-2026-marmor-voxknesset-large-scale-longitudinal-hebrew` · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**0** citations](https://openalex.org/works?filter=cites:W7133304707) openalex · 2026-10-18[**1** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/langstream-2026-marmor-voxknesset-large-scale-longitudinal-hebrew/) of the 140673 papers whose bibliographies we read[arXiv:2603.01270](https://openalex.org/S4306400194)[licence](http://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://arxiv.org/abs/2603.01270)
- [PDF](https://arxiv.org/pdf/2603.01270)
- [arXiv 2603.01270](https://arxiv.org/abs/2603.01270)
- [OpenAlex](https://openalex.org/W7133304707)

**Authors (2)**

1. [Yanir Marmor; Arad Zulti; David Krongauz; Adam Gabet; Yoad Snapir; Yair Lifshitz;](https://openalex.org/A5108851522) h 1 · 1 citations · 3 works
2. [Eran Segal](https://openalex.org/A5012450539) [ORCID](https://orcid.org/0000-0002-6859-1164) · h 105 · 71977 citations · 530 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

The authors release VoxKnesset, a speech corpus of about 2,300 hours from Israeli parliamentary plenary recordings (2009–2025). It covers 393 members of the Knesset, and many speak across up to 15 years. Each segment has word-level forced alignment from Whisper with a confidence score, and verified birth year and gender from official records. The speaker split is 80/20, so that all sessions of one speaker stay in one partition. The paper benchmarks WavLM-Large, ECAPA-TDNN and Wav2Vec2-XLSR-1B on age prediction and speaker verification. Age prediction gives an MAE of 6.3 years in-domain. Speaker-verification EER rises from 2.15% to 4.58% over 15 years for the strongest model. Cross-sectional age regressors do not follow within-speaker aging, but a longitudinal model recovers a usable signal. The paper is about speech, and Mova does not process audio.

## Ideas

- I1. Split by speaker or by document, never by segment. Any Hebrew test set Mova builds should keep all material from one author or one source document in one partition, so that the held-out result is not inflated by near-duplicate text.
- I2. Use the confidence-based filter from the alignment pipeline as a rule for corpus building: drop segments whose median word confidence is low, and drop length outliers beyond 1.5 times the interquartile range. Measure how many sentences a Hebrew corpus loses under this rule.
- I3. Use the parliamentary transcripts as a formal-register check for Modern Hebrew. They are non-verbatim, so they are good for register and lexicon statistics, but not for parsing gold.

## For Mova

I1 and I2 go into the corpus and test builder shared by the Hebrew crates (`treebanks/he/` tooling, and the held-out rule in the release checks). I3 goes into [8. Lexicon and register](https://md.mova.elamur.ai/free/en/docs/languages/he/08-lexicon-register/) as a register corpus. The speech models are out of scope.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [arXiv 2603.01270](https://arxiv.org/abs/2603.01270)

```
@misc{lifshitz2026voxknesset,
  title = {{VoxKnesset: A Large-Scale Longitudinal Hebrew Speech Dataset for Aging Speaker Modeling}},
  author = {Lifshitz;, Yanir Marmor; Arad Zulti; David Krongauz; Adam Gabet; Yoad Snapir; Yair and Segal, Eran},
  year = {2026},
  eprint = {2603.01270},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2603.01270}
}
```

- [← previous When Similar Means Different: Evaluating LLMs on Arabic–Hebrew Cognates](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2026-liang-similar-means-different-evaluating-llms/)
- [next → ReNikud: Audio-Supervised Hebrew Grapheme-to-Phoneme Conversion](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2026-melichov-renikud-audio-supervised-hebrew-grapheme/)
- [↑ back to Modern Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/he/)

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