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端到端语音识别模型的设计与实现

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阐述一种基于注意力机制的端到端语音识别模型,采用编码器-解码器架构,可直接将语音信号转换为文本.在Librispeech数据集中,该模型的字错误率低于5.8%,优于大多数传统语音识别系统.
Design and Implementation of an End to End Speech Recognition Model
This paper describes an end-to-end speech recognition model based on attention mechanism,which adopts an encoder decoder architecture and can directly convert speech signals into text.In the Librispeech dataset,the model achieved a word error rate of 5.8%,which is better than most traditional speech recognition systems.

speech recognitionend-to-end modelattention mechanismdeep learningencoder decoder architecture

刘帅

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山东凌然智能科技有限公司,山东 264006

语音识别 端到端模型 注意力机制 深度学习 编码器-解码器架构

2024

电子技术
上海市电子学会,上海市通信学会

电子技术

影响因子:0.296
ISSN:1000-0755
年,卷(期):2024.53(8)