jefflai108/Semi-Supervsied-Spoken-Language-Understanding-PyTorch
Semi-supervised spoken language understanding (SLU) via self-supervised speech and language model pretraining
This project helps build spoken language understanding systems that can interpret user commands, even with limited labeled data. It takes raw audio of speech and transcribes it, extracting the intent and specific details (like a city name or product). This is useful for anyone creating voice assistants, interactive voice response (IVR) systems, or other speech-driven applications.
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Use this if you need to develop a voice assistant or IVR system that understands spoken commands, but you have difficulty collecting large amounts of labeled speech data.
Not ideal if you are looking for a general-purpose speech-to-text transcriber without needing to extract specific intents or 'slots' of information.
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12
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4
Language
Python
License
MIT
Category
Last pushed
Mar 23, 2021
Commits (30d)
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