The dataset was curated from internet sources and processed using automatic alignment techniques. It contains Bahnar speech audio paired with Vietnamese translations.

For more details on the data creation process, please refer to the dataset README and repository below.

Usage with Transformers

python

import torch
import soundfile as sf
from transformers import AutoProcessor, SeamlessM4Tv2ForSpeechToText

model_id = "cuong06/seamlessm4t-v2-Bahnar-Vietnamese"

processor = AutoProcessor.from_pretrained(model_id)
model = SeamlessM4Tv2ForSpeechToText.from_pretrained(model_id)

audio, sampling_rate = sf.read("sample.wav")

inputs = processor(
    audio=audio,
    sampling_rate=sampling_rate,
    return_tensors="pt"
)

with torch.no_grad():
    predicted_ids = model.generate(
        **inputs,
        tgt_lang="vie"
    )

translation = processor.batch_decode(
    predicted_ids,
    skip_special_tokens=True
)[0]

print(translation)

Evaluation

Results on the test set using beam search (beam_size=5):

Metric	Score
BLEU	24.58

sacreBLEU Signature

Limitations

The dataset was automatically collected and aligned from internet sources, so some noisy samples may remain.
Performance may degrade on unseen dialects, noisy audio, or long-form speech.
This model is intended only for Bahnar → Vietnamese speech translation.

Citation

If you use this model or the dataset, please cite the repository and dataset.

Repository

bibtex

@misc{bahnar_vietnamese_s2tt,
  author = {Dam Cuong},
  title = {Bahnar-Vietnamese Speech-to-Text Translation},
  year = {2026},
  howpublished = {\url{https://github.com/damcuong8/Bahnar-Vietnamese-S2TT}}
}

cuong06/seamlessm4t-v2-Bahnar-Vietnamese

SeamlessM4T-v2 Bahnar-Vietnamese S2TT

Model Details

Dataset