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Wav2vec2 Base Keyword Spotting
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Wav2vec2 Base Keyword Spotting

Developed by anton-l
A fine-tuned speech keyword recognition model based on wav2vec2-base on the superb dataset, achieving 98.43% accuracy
Audio Classification
Transformers
Open Source License:Apache-2.0#Audio Keyword Recognition#High Accuracy#Voice Command Detection
Downloads 14
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned model for speech keyword recognition, based on Facebook's wav2vec2-base architecture, trained on the superb dataset, capable of efficiently recognizing keywords in speech.

Model Features

High Accuracy
Achieves 98.43% accuracy on the evaluation set, demonstrating excellent performance
Based on wav2vec2 Architecture
Uses Facebook's open-source wav2vec2-base model as the foundational architecture
Efficient Training
Optimizes training efficiency using techniques like mixed-precision training and gradient accumulation

Model Capabilities

Speech Keyword Recognition
Audio Classification

Use Cases

Voice Interaction
Voice Assistant Wake Word Detection
Used to detect device wake words, such as 'Hey Siri'
High accuracy in recognizing specific keywords
Voice Command Recognition
Recognizes key command words in voice instructions
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