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This project is a voiceprint recognition system based on PaddlePaddle. It covers application scenarios from data preprocessing, model training to voiceprint recognition and comparison, and is suitable

This paper introduces a method for adding punctuation marks to speech recognition text according to grammar, mainly divided into four steps: downloading and decompressing the model, installing PaddleN

This document introduces how to deploy and test a speech recognition model implemented using PaddlePaddle, and provides various methods to execute and demonstrate the model's functionality. The follow

The WenetSpeech dataset provides over 10,000 hours of Mandarin Chinese speech, categorized into strong-labeled (10,005 hours), weak-labeled (2,478 hours), and unlabeled (9,952 hours) subsets, suitable

This project develops a small and efficient face recognition system based on the ArcFace and PP-OCRv2 models. The training dataset is emore (containing 85,742 individuals and 5,822,653 images), and th

This project aims to develop a face recognition system with small models, high recognition accuracy, and fast inference speed. The training data is sourced from the emore dataset (5.82 million images)

This project is an end-to-end Automatic Speech Recognition (ASR) system implemented based on Kaldi and MindSpore. The system architecture includes multiple stages such as data collection, preprocessin

This code is mainly based on the PaddlePaddle framework and is used to implement a speech recognition system based on acoustic features. The project structure is clear, including functional modules su

This project demonstrates how to use the PaddlePaddle framework for voiceprint recognition, covering multiple steps from model training to application deployment. The following are some key points and

This project well demonstrates how to use deep learning models for voiceprint recognition and voiceprint comparison. Below, I will optimize and improve the code and provide some suggestions to better