PPASR Streaming and Non-Streaming Speech Recognition
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 following is a summary and interpretation of the document content: ### 1. Introduction - Provides an overview of PaddlePaddle-based speech recognition models, including recognition for short voice segments and long audio clips. ### 2. Deployment Methods #### 2.1 Command-line Deployment Two commands are provided to implement different deployment methods: - `python infer_server.
Read MoreEnd-to-End Chinese Speech Recognition Model of DeepSpeech2 Implemented Based on PaddlePaddle
This tutorial provides a detailed introduction to using PaddlePaddle for speech recognition, along with a series of operational guidelines to assist developers from data preparation to model training and online deployment. Below is a brief summary of each step: 1. **Environment Configuration**: Ensure the development environment has installed necessary software and libraries, including PaddlePaddle. 2. **Data Preparation**: - Download and extract the speech recognition dataset. - Process audio files, such as denoising, downsampling, etc. - (Note: The original summary for "processing text" appears to be incomplete in the provided content.)
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