A PyTorch-based Speech Toolkit
On-device Speech-to-Intent engine powered by deep learning
End-to-end spoken language understanding toolkit: a small trainable neural audio codec with RVQ, joint intent-and-slot models over speech features, streaming partial intents, a speech-LLM instruction data pipeline, and turn-level evaluation with reproducible reports. NumPy core with a CPU-only torch extra; synthetic data only, fully offline.
End-to-End Speech Processing Toolkit