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library_name: keras
tags:
- audio-classification
- cnn
- cebuano
- sinama
- mel-spectrogram
pipeline_tag: audio-classification
---
# Sinama Audio Classifier
A CNN-based audio classification model trained to recognise spoken
Cebuano / Sinama words from short audio clips.
## Usage
### Via Inference API
```python
import requests
API_URL = "https://api-inference.huggingface.co/models/YOUR_USERNAME/sinama-translator"
headers = {"Authorization": "Bearer hf_YOUR_TOKEN"}
with open("audio.wav", "rb") as f:
response = requests.post(API_URL, headers=headers, data=f.read())
print(response.json())
# [{"label": "ako", "score": 0.95}, ...]
```
### Local inference
```python
import tensorflow as tf, json, librosa, numpy as np
model = tf.keras.models.load_model("best_model.keras")
with open("label_map.json") as f:
label_map = {int(k): v for k, v in json.load(f).items()}
# preprocess your audio the same way as training …
pred = model.predict(features)
print(label_map[pred.argmax()])
```
## Training details
- **Architecture:** 3-block CNN (Conv2D → BN → ReLU → MaxPool → Dropout)
- **Features:** 128-bin Mel Spectrogram, 4 s clips, 22 050 Hz
- **Optimiser:** Adam
- **Loss:** Categorical cross-entropy
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