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Trillsson3 Ft Keyword Spotting 14
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Trillsson3 Ft Keyword Spotting 14

Developed by vumichien
Audio classification model based on TRillsson3 architecture, fine-tuned on the superb dataset for keyword spotting tasks, achieving 91.5% accuracy.
Audio Classification
Transformers
#Keyword spotting#High-precision audio classification#Non-semantic speech processing
Downloads 47
Release Time : 10/25/2022

Model Overview

This model is a fine-tuned version based on the non-semantic speech representation model TRillsson3, specifically designed for keyword spotting tasks. Trained on the superb dataset, it demonstrates excellent performance on evaluation sets.

Model Features

High accuracy
Achieves 91.5% accuracy on evaluation sets, demonstrating excellent performance
Based on TRillsson3 architecture
Built upon a powerful non-semantic speech representation model
Efficient training
Uses mixed-precision training and Adam optimizer for high training efficiency

Model Capabilities

Audio classification
Keyword spotting
Speech feature extraction

Use Cases

Intelligent voice interaction
Voice assistant wake word detection
Used to detect device wake words like 'Hey Siri' or 'OK Google'
High accuracy ensures successful wake-up rates
Voice control command recognition
Recognizes specific voice commands to control system operations
Speech analysis
Speech content classification
Classifies and tags speech content by keywords
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