Evidano is an AI-powered qualitative data analysis platform that ingests phonemic and orthographic transcripts for thematic, frequency, and cross-segment analysis. Unvocalized Hebrew (no niqqud) is a persistent obstacle for TTS, ASR post-processing, and spoken-language research. ReNikud Plus (published on PyPI on Jul 17, 2026) provides an ONNX-based Hebrew grapheme-to-phoneme conversion model (phonemize → IPA, vocalize → niqqud) that downloads ~310 MB of weights on first use. In this post we show what changed, why it matters for researchers and product teams analyzing Hebrew speech/text, and a short workflow to ingest ReNikud outputs into Evidano for thematic, frequency, and cross-segment analysis. Learn how to convert phonemic outputs into research-ready transcripts and speed synthesis with www.evidano.com.
Key Takeaways
ReNikud Plus is an ONNX-based Python package that converts unvocalized Hebrew to IPA and niqqud for TTS and research workflows. The model weights are approximately 310 MB and download automatically from Hugging Face on first use; the package was uploaded to PyPI on Jul 17, 2026.
- ReNikud Plus provides two outputs: IPA via phonemize and pointed Hebrew (niqqud) via vocalize, with phonemize preserving stress and vocalize omitting some stress marks.
- Model weights (~310 MB) download from Hugging Face on first run, or users can pass a local ONNX file to the API.
- ReNikud Plus was published on PyPI on Jul 17, 2026, and the accompanying research citation is Melichov et al., ReNikud (arXiv:2606.20179, 2026).
- Evidano can ingest ReNikud phonemized IPA and niqqud fields for thematic coding, frequency counts, co-occurrence analysis, and reproducible visual reporting.
Fast take, source & one-line summary
ReNikud Plus is a Python package that runs ONNX inference to convert unvocalized Hebrew text into IPA or niqqud. See the original release page at PyPI.
- Primary use: phonemization for TTS, speech tech, and spoken-language research.
- Model weights (~310 MB) download automatically from Hugging Face on first run.
- Citation: Melichov et al., ReNikud (arXiv:2606.20179, 2026).
Findings snapshot
| Metric | Value | Notes / Source |
|---|---|---|
| PyPI upload date | Jul 17, 2026 | PyPI |
| Package version (files) | renikud_plus-0.3.0 (tar.gz, wheel) | tar.gz 6.2 kB; wheel 7.0 kB |
| ONNX model weights | ~310 MB | Downloaded from Hugging Face on first use |
| Outputs | IPA (phonemize); Niqqud (vocalize) | phonemize preserves stress; vocalize omits stress marks |
| Gender-conditioned option | speaker / target_speaker (0/1/2) | Allows male/female/unknown conditioning |
| Research citation | Melichov et al., 2026 (arXiv) | arXiv |
What ReNikud Plus does (plain English)
ReNikud Plus exposes a small API (G2P class) that runs an ONNX model to map Hebrew graphemes to phonemes. Example usage:
- g2p = G2P(); g2p.phonemize("שלום עולם") → ʃlˈom ʔolˈam
- g2p.vocalize(...) returns pointed Hebrew (niqqud) suitable for TTS engines that accept diacritics.
- If you already host weights, pass a local path: G2P('model.onnx').
Practical caveats: niqqud output is phonetically faithful but not 'publication-grade' and omits some diacritics (for example, shva in clusters). The package supports optional gender-conditioned decoding, which can be useful when modeling speaker-typical vowel realization.
So what for researchers and product teams?
For TTS / speech engineers
ReNikud Plus provides a quick phonemization pipeline: feed unvocalized orthography to ReNikud to produce IPA or niqqud, then pass outputs to a downstream TTS phoneme frontend or grapheme-augmented synthesis. The benefit is reduced manual diacritization effort and improved consistency across corpora.
For spoken-language and corpus researchers
ReNikud Plus standardizes phonemic transcriptions across speakers, enabling frequency counts, co-occurrence analysis, and stress-pattern studies. ReNikud Plus is useful as an audio-supervised G2P baseline, as noted in the package citation.
For qualitative researchers and UX teams analyzing Hebrew speech
ReNikud Plus transforms unreadable unvocalized text into phonemically explicit transcripts that are easier to code for pronunciation features, emphasis, or lexical ambiguity. ReNikud Plus enables combined thematic and phonetic analysis when transcripts are aligned to audio.
Do more, faster with Evidano (map to your use case)
Ingest & align
Evidano accepts ReNikud phonemized outputs or niqqud transcripts alongside audio transcripts. Evidano accepts text files and spreadsheet survey exports and can keep phoneme fields linked to original utterances for segment-level analysis.
Cross-segment thematic + phonetic analysis
Evidano enables running thematic coding on orthographic text while using an IPA field for frequency counts and co-occurrence networks, for example stressed syllables versus theme prevalence. Evidano produces hierarchical code trees and co-occurrence visualizations that surface links between phonetic patterns and topics.
Transcription, translation, and PII-safe workflows
Evidano provides transcription with custom dictionaries, PII redaction, and bidirectional translation to keep niqqud and IPA consistent across languages. All data in Evidano is encrypted and never used to train external models.
Autonomous follow-ups
Evidano supports AI avatar interviewers to collect targeted follow-ups and feed responses back into the same corpus for iterative coding.
Quick integration checklist
Follow these steps to operationalize ReNikud outputs into an AI-enabled qualitative pipeline:
- Install and run ReNikud (pip install renikud-plus); cache ONNX weights locally (~310 MB).
- Phonemize your unvocalized corpus and save IPA and/or niqqud as separate fields.
- Import transcripts and phoneme fields into Evidano (text or CSV).
- Auto-code with Evidano to generate initial themes, then add manual codes where phonetics matter.
- Run frequency, co-occurrence, and cross-segment analyses, for example by speaker gender, region, or condition.
- Visualize results with word clouds and co-occurrence networks, and extract example quotes linked to IPA contexts.
- If needed, collect targeted follow-ups with Evidano AI avatars to probe phonetic or lexical patterns.
FAQ: Hebrew grapheme-to-phoneme conversion
What is ReNikud Plus and what does it do?
ReNikud Plus is a Python package that runs an ONNX model to map unvocalized Hebrew graphemes to phonemes, producing IPA or pointed Hebrew (niqqud). The package exposes a small API (G2P class) with methods such as phonemize and vocalize for transliteration and diacritization.
When was ReNikud Plus released and where can I find it?
What outputs does ReNikud Plus provide and how do they differ?
ReNikud Plus outputs IPA via phonemize and niqqud via vocalize, with phonemize preserving stress and vocalize omitting some stress marks. Niqqud output is phonetically faithful but omits certain diacritics and may not be publication-grade for all linguistic analyses.
How large are the model weights and how are they accessed?
The ONNX model weights are approximately 310 MB and download automatically from Hugging Face on first use. Users who already host weights can pass a local ONNX path to the G2P API, for example G2P('model.onnx').
How do I integrate ReNikud outputs with Evidano?
Import ReNikud phonemized IPA or niqqud transcripts into Evidano as text or CSV fields and link phoneme fields to original utterances for segment-level analysis. Use Evidano to run thematic coding, frequency counts, co-occurrence analysis, and to visualize links between phonetic patterns and topics.
Ethics & validation note
Automated phonemization is a research tool, not a clinical or definitive linguistic judgment. Validate model outputs on a representative sample of your corpus, especially when working with dialectal Hebrew or sociophonetic studies. For citation and model details see the package page on PyPI and the accompanying paper on arXiv.
Wrapping up, next steps
ReNikud Plus (PyPI release Jul 17, 2026) lowers the barrier to producing IPA and niqqud from unvocalized Hebrew. For teams that analyze Hebrew speech or combine phonetics with thematic coding, pairing ReNikud outputs with Evidano accelerates synthesis, cross-segment comparisons, and reproducible visual reporting.
Ready to try it on your corpus? Import your ReNikud phoneme fields into Evidano and run thematic and frequency analyses in minutes: Try Evidano for free.