AI & ML interests

Hebrew, LLM, speech recognition

Recent Activity

benderrodriguezΒ  updated a bucket about 12 hours ago
ivrit-ai/tts-arena-cache
benderrodriguezΒ  updated a dataset 1 day ago
ivrit-ai/tts-arena-preferences
yoadΒ  updated a dataset 15 days ago
ivrit-ai/eval-forced-alignment
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Organization Card

ivrit.ai β€” open Hebrew speech & language AI

ivrit.ai is a non-profit building open, permissively licensed Hebrew (and Yiddish) datasets and models. Models: apache-2.0. Datasets: the ivrit.ai License (v2) β€” which allows broad research and commercial use.

πŸš€ Start here β€” which model should I use?

I want to… Use Runtime
Transcribe Hebrew fast on GPU/CPU whisper-large-v3-turbo-ct2 faster-whisper
Get the best Hebrew accuracy whisper-large-v3 transformers
Run on a laptop / whisper.cpp whisper-large-v3-turbo-ggml whisper.cpp
Run in the browser / ONNX whisper-large-v3-turbo-onnx onnxruntime
Real-time / on-device streaming zipformer2-66m-streaming-he sherpa-onnx
Who spoke when (diarization) pyannote-speaker-diarization-3.1 pyannote.audio
Transcribe Yiddish yi-whisper-large-v3-turbo transformers
# pip install faster-whisper
from faster_whisper import WhisperModel
model = WhisperModel("ivrit-ai/whisper-large-v3-turbo-ct2")
segments, _ = model.transcribe("audio.wav", language="he")
print(" ".join(s.text for s in segments))

No code? Try it in .

πŸ“Š Leaderboards & arenas

πŸ—‚οΈ Datasets

Collection What's inside
Hebrew ASR training crowd-transcribe-v5, crowd-recital, whisper-training
Knesset speech knesset-plenums, VoxKnesset, knesset-committees
Raw audio corpus audio-v2 (+ opus, transcripts)
Evaluation eval-d1, eval-whatsapp, eval-forced-alignment
Yiddish crowd-recital-yi, crowd-whatsapp-yi
OCR & TTS hebrew-handwriting-ocr-benchmark, tts-arena-preferences

Older versions stay online but are marked Deprecated on their cards.

🀝 Contribute

  • Record or transcribe Hebrew at ivrit.ai
  • Code & issues: GitHub
  • Questions: open a Discussion on any repo or email to info at ivrit.ai

πŸ“ Cite

Marmor, Lifshitz, Snapir, Misgav. Building an Accurate Open-Source Hebrew ASR System through Crowdsourcing. Interspeech 2025. doi:10.21437/Interspeech.2025-460

ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and Development β€” arXiv:2307.08720