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README.md

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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