| # DiariZen Speaker Segmentation SDK | |
| CPU+NPU hybrid speaker diarization segmentation inference. | |
| ## Architecture | |
| ``` | |
| Audio (16kHz mono, 4s) | |
| → CPU LayerNorm preprocessing | |
| → AX650 NPU CNN feature extractor (U16) | |
| → CPU WavLM Transformer + Conformer + Classifier (FP32, ONNX Runtime) | |
| → Frame-level log-probabilities (1, 199, 11) | |
| ``` | |
| ## Requirements | |
| - Python 3.8+ | |
| - numpy, onnxruntime, soundfile | |
| - pyaxengine (for NPU inference) | |
| ## Usage | |
| ```python | |
| from diarizen_sdk import DiarizenSegmenter | |
| segmenter = DiarizenSegmenter("cnn_features.axmodel", "backend.onnx") | |
| log_probs = segmenter(audio_array, sample_rate=16000) | |
| # log_probs: (1, 199, 11) float32 | |
| ``` | |