Finnish Wav2vec2-XLarge ASR
GetmanY1/wav2vec2-xlarge-fi-150k fine-tuned on 4600 hours of Finnish speech on 16kHz sampled speech audio:
- 1500 hours of Lahjoita puhetta (Donate Speech) (colloquial Finnish)
- 3100 hours of the Finnish Parliament dataset
When using the model make sure that your speech input is also sampled at 16Khz.
Model description
The Finnish Wav2Vec2 X-Large has the same architecture and uses the same training objective as the multilingual one described in paper.
GetmanY1/wav2vec2-xlarge-fi-150k is a large-scale, 1-billion parameter monolingual model pre-trained on 158k hours of unlabeled Finnish speech, including KAVI radio and television archive materials, Lahjoita puhetta (Donate Speech), Finnish Parliament, Finnish VoxPopuli.
You can read more about the pre-trained model from this paper. The training scripts are available on GitHub.
Intended uses
You can use this model for Finnish ASR (speech-to-text).
How to use
To transcribe audio files the model can be used as a standalone acoustic model as follows:
from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC
from datasets import load_dataset
import torch
# load model and processor
processor = Wav2Vec2Processor.from_pretrained("GetmanY1/wav2vec2-xlarge-fi-150k-finetuned")
model = Wav2Vec2ForCTC.from_pretrained("GetmanY1/wav2vec2-xlarge-fi-150k-finetuned")
# load dummy dataset and read soundfiles
ds = load_dataset("mozilla-foundation/common_voice_16_1", "fi", split='test')
# tokenize
input_values = processor(ds[0]["audio"]["array"], return_tensors="pt", padding="longest").input_values # Batch size 1
# retrieve logits
logits = model(input_values).logits
# take argmax and decode
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.batch_decode(predicted_ids)
Citation
If you use our models or scripts, please cite our article as:
@inproceedings{getman25_interspeech,
title = {{Is your model big enough? Training and interpreting large-scale monolingual speech foundation models}},
author = {{Yaroslav Getman and Tamás Grósz and Tommi Lehtonen and Mikko Kurimo}},
year = {{2025}},
booktitle = {{Interspeech 2025}},
pages = {{231--235}},
doi = {{10.21437/Interspeech.2025-46}},
issn = {{2958-1796}},
}
Team Members
- Yaroslav Getman, Hugging Face profile, LinkedIn profile
- Tamas Grosz, Hugging Face profile, LinkedIn profile
Feel free to contact us for more details 🤗