gigant/romanian-wav2vec2
automatic-speech-recognition model by gigant
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Model card & documentation
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You can test this model online with the Space for Romanian Speech Recognition The model ranked TOP-1 on Romanian Speech Recognition during HuggingFace's Robust Speech Challenge : This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the Common Voice 8.0 - Romanian subset dataset, with extra training data from Romanian Speech Synthesis dataset. Without the 5-gram Language Model optimization, it achieves the following results on the evaluation set (Common Voice 8.0, Romanian subset, test split): The architecture is based on facebook/wav2vec2-xls-r-300m with a speech recognition CTC head and an added 5-gram language model (using pyctcdecode and kenlm) trained on the Romanian Corpora Parliament dataset. Those libraries are needed in order for the language model-boosted decoder to work. The model is made for speech recognition in Romanian from audio clips sampled at 16kHz. The predicted text is lowercased and does not contain any punctuation. Make sure you have installed…
Read the full model card ↗ · Preview checked 2026-10-29T12:53:29.910Z
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Model overview
gigant/romanian-wav2vec2 is a automatic-speech-recognition model repository published by gigant on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- automatic-speech-recognition
- Library
- transformers
- Recent downloads (30 days)
- 1,391,947
- Cumulative likes
- 21
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 315,475,620
- Architecture
- Wav2Vec2ForCTC
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2023-09-13T11:45:00.000Z
Compatibility and lineage
Reported languages: ro
Reported base models: facebook/wav2vec2-xls-r-300m
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:32.899Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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