检索结果-南通市图书馆

Joint On-Demand Pruning and Online Distillation in Automatic Speech Recognition language model Optimization

Computers, Materials & Continua 2023年第12期77卷 2833-2856页

作者： Soonshin Seo Ji-Hwan Kim Clova Speech Naver CorporationSeongnam13561Korea Department of Computer Science and Engineering Sogang UniversitySeoul04107Korea

Automatic speech recognition(ASR)systems have emerged as indispensable tools across a wide spectrum of applications,ranging from transcription services to voice-activated *** enhance the performance of these systems,it is important to deploy efficient models capable of adapting to diverse deployment *** recent years,on-demand pruning methods have obtained significant attention within the ASR domain due to their adaptability in various deployment ***,these methods often confront substantial trade-offs,particularly in terms of unstable accuracy when reducing the model *** address challenges,this study introduces two crucial empirical ***,it proposes the incorporation of an online distillation mechanism during on-demand pruning training,which holds the promise of maintaining more consistent accuracy ***,it proposes the utilization of the Mogrifier long short-term memory(LSTM)language model(LM),an advanced iteration of the conventional LSTM LM,as an effective alternative for pruning targets within the ASR *** rigorous experimentation on the ASR system,employing the Mogrifier LSTM LM and training it using the suggested joint on-demand pruning and online distillation method,this study provides compelling *** results exhibit that the proposed methods significantly outperform a benchmark model trained solely with on-demand pruning ***,the proposed strategic configuration successfully reduces the parameter count by approximately 39%,all the while minimizing trade-offs.

关键词： Automatic speech recognition neural language model Mogrifier long short-term memory pruning distillation efficient deployment optimization joint training

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：