---
tags:
- audio-classification
- speech-classification
- audio
- chunkformer
- pytorch
- transformers
- speech-processing
- age
- dialect
- emotion
- gender

license: apache-2.0
library_name: transformers
pipeline_tag: audio-classification
---

# ChunkFormer Classification Model
<style>
img {
display: inline;
}
</style>
[![GitHub](https://img.shields.io/badge/GitHub-ChunkFormer-blue)](https://github.com/khanld/chunkformer)
[![Paper](https://img.shields.io/badge/Paper-ICASSP%202025-green)](https://arxiv.org/abs/2502.14673)

This model performs speech classification tasks such as gender recognition, dialect identification, emotion detection, and age classification.

## Classification Tasks

- **Age**: 5 classes
- **Dialect**: 5 classes
- **Emotion**: 8 classes
- **Gender**: 2 classes


## Usage

Install the package:

```bash
pip install chunkformer
```

### Single Audio Classification

```python
from chunkformer import ChunkFormerModel

# Load the model
model = ChunkFormerModel.from_pretrained("khanhld/chunkformer-gender-emotion-dialect-age-classification")

# Classify a single audio file
result = model.classify_audio(
    audio_path="path/to/your/audio.wav",
    chunk_size=-1,  # -1 for full attention
    left_context_size=-1,
    right_context_size=-1
)

print(result)
# Output example:
# {
#   'gender': {
#       'label': 'female',
#       'label_id': 0,
#       'prob': 0.95
#   },
#   'dialect': {
#       'label': 'northern dialect',
#       'label_id': 3,
#       'prob': 0.70
#   },
#   'emotion': {
#       'label': 'neutral',
#       'label_id': 5,
#       'prob': 0.80
#   }
# }
```

### Command Line Usage

```bash
chunkformer-decode \
    --model_checkpoint khanhld/chunkformer-gender-emotion-dialect-age-classification \
    --audio_file path/to/audio.wav
```

## Training

This model was trained using the ChunkFormer framework. For more details about the training process and to access the source code, please visit: https://github.com/khanld/chunkformer

Paper: https://arxiv.org/abs/2502.14673

## Citation

If you use this work in your research, please cite:

```bibtex
@INPROCEEDINGS{10888640,
    author={Le, Khanh and Ho, Tuan Vu and Tran, Dung and Chau, Duc Thanh},
    booktitle={ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
    title={ChunkFormer: Masked Chunking Conformer For Long-Form Speech Transcription},
    year={2025},
    volume={},
    number={},
    pages={1-5},
    keywords={Scalability;Memory management;Graphics processing units;Signal processing;Performance gain;Hardware;Resource management;Speech processing;Standards;Context modeling;chunkformer;masked batch;long-form transcription},
    doi={10.1109/ICASSP49660.2025.10888640}}
```