Open-source Speech Recognition Model wav2vec2-base-finetuned-ks

Wav2vec2 Base Finetuned Ks

Developed by Dc26

A speech recognition model fine-tuned on the speech_commands dataset based on facebook/wav2vec2-base, achieving 97.8% accuracy

Audio Classification

Transformers

Open Source License:Apache-2.0 #Voice command recognition #High accuracy #Audio classification

Downloads 23

Release Time : 3/25/2023

Model Overview

This model is a fine-tuned model for voice command recognition, based on the wav2vec2 architecture, suitable for keyword detection tasks

Model Features

High accuracy

Achieves 97.8% accuracy on the evaluation set

Based on wav2vec2 architecture

Uses the powerful wav2vec2-base as the base model

Lightweight fine-tuning

Requires only a small amount of training data to achieve good performance

Model Capabilities

Voice command recognition

Keyword detection

Audio classification

Use Cases

Smart home

Voice-controlled devices

Recognizes user voice commands to control smart home devices

Accurately recognizes common control commands

Wearable devices

Voice assistant

Implements basic voice interaction functions on resource-constrained devices

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6408	1.0	2651	0.2399	0.9609
0.4113	2.0	5303	0.1284	0.9686
0.3014	3.0	7954	0.1144	0.9706
0.2914	4.0	10606	0.0962	0.9760
0.1621	5.0	13255	0.0880	0.9780

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Wav2vec2 Base Finetuned Ks

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 wav2vec2-base-finetuned-ks

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