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Distilhubert Ft Keyword Spotting
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Distilhubert Ft Keyword Spotting
Developed by anton-l
Keyword recognition model based on the DistilHuBERT architecture, fine-tuned on the superb dataset with an accuracy of 97.06%
Downloads 14
Release Time : 3/2/2022
Model Overview
This is an audio classification model for keyword recognition tasks, based on the lightweight DistilHuBERT architecture and fine-tuned on the superb dataset.
Model Features
High Accuracy
Achieves 97.06% accuracy on the evaluation set
Lightweight Architecture
Based on the DistilHuBERT architecture, more lightweight compared to the original HuBERT model
Efficient Training
Uses mixed-precision training to optimize training efficiency
Model Capabilities
Audio Classification
Keyword Recognition
Voice Command Detection
Use Cases
Smart Home
Voice-Controlled Devices
Recognizes specific wake words to control smart home devices
High accuracy in recognizing user commands
Voice Assistants
Wake Word Detection
Detects device wake words to activate voice assistants
Low false alarm rate and high recall rate
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