Instructions to use renikud/whisper-he-ipa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use renikud/whisper-he-ipa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="renikud/whisper-he-ipa")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("renikud/whisper-he-ipa") model = AutoModelForSpeechSeq2Seq.from_pretrained("renikud/whisper-he-ipa") - Notebooks
- Google Colab
- Kaggle
whisper-he-ipa
This model predicts IPA phonemes transcription from Hebrew speech.
It was fine-tuned from ivrit-ai/whisper-large-v3-turbo.
Output format
The model outputs ASCII Hebrew IPA, using ASCII-safe symbols instead of some IPA characters.
After normalization, the Hebrew IPA phoneme inventory is:
abdefhijklmnopstuvwzɡʁʃʒʔˈχ
Mapping from model output to normalized IPA:
ASCII_TO_IPA = {
"dZ": "dʒ",
"tS": "tʃ",
"S": "ʃ",
"Z": "ʒ",
"q": "ʔ",
"'": "ˈ",
"r": "ʁ",
"x": "χ",
"g": "ɡ",
}
Example:
Input: שלום עולם
Model output: Sal'om qol'am
Normalized IPA: ʃalˈom ʔolˈam
Citation
@misc{melichov2026renikud,
title={ReNikud: Audio-Supervised Hebrew Grapheme-to-Phoneme Conversion},
author={Maxim Melichov and Yakov Kolani and Morris Alper},
year={2026},
note={Code and models forthcoming},
}
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Model tree for renikud/whisper-he-ipa
Base model
openai/whisper-large-v3 Finetuned
openai/whisper-large-v3-turbo Finetuned
ivrit-ai/whisper-large-v3-turbo