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MobiDev:如何有效搭建语音识别系统(2022)(中译版)(15页).pdf

上传人: Kell****reet 编号:106371 2022-11-15 15页 3.08MB

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1、Table of ContentsVOICE RECOGNITION VS SPEECH RECOGNITIONHow do speech recognition applications work?WHICH TYPE OF AI IS USED IN SPEECH RECOGNITION?WHAT IS IMPORTANT FOR SPEECH RECOGNITION TECHNOLOGY?Automatic Speech Recognition process and componentsOur 4 recommendations for improving quality of ASR

2、1.PAY ATTENTION TO THE SAMPLE RATE2.NORMALIZE RECORDING VOLUME3.IMPROVE RECOGNITION OF SHORT WORDS4.USE NOISE SUPPRESSION METHODS ONLY WHEN NEEDEDGet the enhanced ASR system1Modern voice applications use AI algorithms to recognize different sounds,including human voice and speech.In technical terms,

3、most of the voice appsperform either voice recognition or speech recognition.And while there is no bigdifference between the architecture and AI models that perform voice/speechrecognition,they actually relate to different business tasks.So first of all,let uselaborate on the difference between them

4、.VOICE RECOGNITION VS SPEECH RECOGNITIONVoice recognition is the ability to single out specific voices from other sounds,and identify the owners tone to implement security features like voicebiometrics.Speech recognition is mostly responsible for extracting meaningful informationfrom the audio,recog

5、nizing the words said,and the context they are placed in.With this we can create systems like chatbots and virtual assistants forautomated communication and precise understanding of voice commands.Both terms can often be used interchangeably,because there is not muchtechnical difference between the

6、algorithms that perform these functions.Although,depending on what you need,the pipeline for voice or speechrecognition may be different in terms of processing steps.If you are interestedin voice recognition for security systems specifically,read our article on AI voicebiometrics:In this post,well f

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本文主要探讨了语音识别技术及其在现代语音应用程序中的应用,如虚拟助手和聊天机器人。文章首先阐述了语音识别与声音识别之间的区别,然后详细介绍了自动语音识别(ASR)的工作原理和组成部分。ASR技术利用AI模型将语音转换为文本,进而应用自然语言处理(NLP)。文章还强调了在开发ASR系统时应考虑的几个关键因素,包括音频文件格式、采样率、录音音量、短词识别和噪声抑制等。为了提高ASR系统的质量,作者提出了四点建议:关注采样率、标准化录音音量、改进短词识别和谨慎使用噪声抑制方法。最后,文章指出,在构建ASR系统时,应充分考虑实际应用场景和需求,以实现最优的识别效果。
"语音识别与说话人识别有何不同?" "如何提高语音识别技术的准确性?" "语音识别技术在实际应用中需要注意哪些问题?"
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