JavaShuo
欄目
標籤
Language Identification with Deep Bottleneck Features
時間 2020-12-23
標籤
paper筆記
简体版
原文
原文鏈接
時間:2018.9 沒看到發佈的地址 作者:Zhanyu Ma, Hong Yu abstract 用於中文音素分類的DNN的bottleneck特徵被用於LSTM的訓練。 1. introduction SLD任務用在語音識別的前端,首先判別一句話的語種,然後喚醒對應的decode去翻譯成文本。 世界上有上千種語言,每種語言有不同的區分特徵,想要找到一種通用的,快速響應的有效SLD system
>>阅读原文<<
相關文章
1.
深度學習之Bottleneck Layer or Bottleneck Features
2.
BN for Language Identification
3.
Learning Transferable Features with Deep Adaptation Networks
4.
Large-Scale and Language-Oblivious Code Authorship Identification
5.
【Person Re-ID】Deep-Person: Learning Discriminative Deep Features for Person Re-Identification
6.
[c++] C Language Features
7.
【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification
8.
翻譯「Learning Transferable Features with Deep Adaptation Networks」
9.
Content-based image retrieval with compact deep convolutional features
10.
Deep Reinforcement Learning with a Natural Language Action Space
更多相關文章...
•
RSS
元素
-
RSS 教程
•
XSLT
元素
-
XSLT 教程
•
YAML 入門教程
•
爲了進字節跳動,我精選了29道Java經典算法題,帶詳細講解
相關標籤/搜索
language
identification
bottleneck
features
deep
with+this
with...connect
with...as
by...with
Deep Learning
MyBatis教程
0
分享到微博
分享到微信
分享到QQ
每日一句
每一个你不满意的现在,都有一个你没有努力的曾经。
最新文章
1.
ubantu 增加搜狗輸入法
2.
用實例講DynamicResource與StaticResource的區別
3.
firewall防火牆
4.
頁面開發之res://ieframe.dll/http_404.htm#問題處理
5.
[實踐通才]-Unity性能優化之Drawcalls入門
6.
中文文本錯誤糾正
7.
小A大B聊MFC:神奇的靜態文本控件--初識DC
8.
手扎20190521——bolg示例
9.
mud怎麼存東西到包_將MUD升級到Unity 5
10.
GMTC分享——當插件化遇到 Android P
本站公眾號
歡迎關注本站公眾號,獲取更多信息
相關文章
1.
深度學習之Bottleneck Layer or Bottleneck Features
2.
BN for Language Identification
3.
Learning Transferable Features with Deep Adaptation Networks
4.
Large-Scale and Language-Oblivious Code Authorship Identification
5.
【Person Re-ID】Deep-Person: Learning Discriminative Deep Features for Person Re-Identification
6.
[c++] C Language Features
7.
【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification
8.
翻譯「Learning Transferable Features with Deep Adaptation Networks」
9.
Content-based image retrieval with compact deep convolutional features
10.
Deep Reinforcement Learning with a Natural Language Action Space
>>更多相關文章<<