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Published "VoiceKey: Real-time Compression Encoding and Quantization for Voice Authentication Model on Edge Devices" at The 4th Korea Artificial Intelligence Conference.

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daehwa00/VoiceKey

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VoiceKey: Your Voice, Your Key

Overview

VoiceKey: Real-time Compression Encoding and Quantization for Voice Authentication Model on Edge Devices" at The 4th Korea Artificial Intelligence Conference Code. 제 4회 한국인공지능학회 "VoiceKey: 엣지 디바이스의 음성 인증 모델을 위한 실시간 압축 인코딩 및 양자화" 코드입니다.

VoiceKey is a cutting-edge voice authentication system that uses encoded voice data to verify identity. It leverages the unique characteristics of each individual's voice to provide a secure and convenient method for user authentication.

Features

  • Voice Authentication: VoiceKey uses advanced machine learning algorithms to analyze the unique features of a user's voice for authentication.

  • Encoded Voice Data: Instead of using raw audio data, VoiceKey uses encoded voice data, which provides a more efficient and secure method for voice authentication.

  • Attention Mechanism: VoiceKey employs an attention mechanism to focus on the most relevant features of the voice data during the authentication process.

Installation

To install VoiceKey, clone the repository and install the required packages:

git clone https://github.com/daehwa00/VoiceKey.git
cd VoiceKey
pip install -r requirements.txt

Usage

To use VoiceKey, follow these steps:

  1. Record or upload your voice data.
  2. The system will encode your voice data and extract the unique features.
  3. Your voice data will be used for authentication.

Contributing

Contact

If you have any questions or feedback, please feel free to contact me

Acknowledgements

We would like to thank all the contributors who have helped to develop and improve VoiceKey.


Please note that this is a basic template for a README file. You may want to customize it according to your project's specific requirements and features.

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Published "VoiceKey: Real-time Compression Encoding and Quantization for Voice Authentication Model on Edge Devices" at The 4th Korea Artificial Intelligence Conference.

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