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查看斯高帕斯 (Scopus) 概要
簡 仁宗
教授
電機工程學系
https://orcid.org/0000-0003-3466-8941
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4426
引文
31
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2259
引文
24
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708
引文
15
h-指數
按照存儲在普爾（Pure）的出版物數量及斯高帕斯（Scopus）引文計算。
1995 …
2026
每年研究成果
概覽
指紋
網路
計畫
(26)
研究成果
(318)
獎項
(18)
活動
(11)
類似的個人檔案
(6)
指紋
查看啟用 Jen-Tzung Chien 的研究主題。這些主題標籤來自此人的作品。共同形成了獨特的指紋。
排序方式
重量
按字母排序
Computer Science
Speech Recognition
100%
Language Modeling
56%
Neural Network
37%
Experimental Result
31%
Recurrent Neural Network
30%
Bayesian Learning
22%
Speaker Verification
21%
Reinforcement Learning
21%
Contrastive Learning
21%
Sequential Learning
20%
Regularization
18%
Leaning Parameter
18%
Dialog System
17%
Domain Adaptation
17%
Adaptation Data
16%
Source Separation
16%
Deep Neural Network
15%
Machine Learning
14%
Latent Dirichlet Allocation
14%
Speaker Recognition
13%
maximum-likelihood
13%
Variational Autoencoder
13%
Feature Extraction
12%
Meta-Learning
12%
Linear Discriminant Analysis
12%
Independent Component Analysis
12%
Training Data
12%
Mutual Information
12%
nonnegative matrix factorization
12%
Natural Language Understanding
11%
Learning System
11%
Autoencoder
11%
Diffusion Model
11%
Attention (Machine Learning)
11%
Telephone
10%
Adversarial Machine Learning
10%
Learning Algorithm
10%
Model Adaptation
10%
Long Short-Term Memory Network
10%
Text To Speech
10%
Latent Variable Model
9%
Classification Accuracy
9%
Seq2Seq
9%
Data Augmentation
9%
Transformation Parameter
8%
Self-Attention
8%
Recognition Performance
8%
Deep Learning Method
8%
Blind Signal Separation
8%
Information Retrieval
8%
Keyphrases
Speech Recognition
53%
Hidden Markov Model
40%
Adaptation
21%
End-to-end Speech Recognition
15%
Language Modeling
13%
Language Model
12%
Speaker Adaptation
12%
Bayesian Learning
11%
Variational
11%
Non-negative Matrix Factorization
10%
International Cooperative Ataxia Rating Scale (ICARS)
10%
Telephone Speech
10%
Hyperparameters
9%
Variational Autoencoder
9%
Maximum a Posteriori
9%
Sequential Learning
9%
Latent Dirichlet Allocation
8%
Neural Network
8%
N-gram
7%
Contrastive Learning
7%
Latent Variables
7%
Latent Topics
7%
Token
7%
Acoustic Modeling
7%
Speaker Recognition
7%
Speaker Verification
7%
Temporal Convolutional Network
7%
Natural Language
6%
Automatic Speech Recognition
6%
Domain Adaptation
6%
Sequence Data
6%
Latent Variable Models
6%
Speaker Characteristics
6%
Dialogue Policy
6%
Attention Mechanism
6%
Target Domain
6%
Large Vocabulary Continuous Speech Recognition (LVCSR)
6%
Recurrent Neural Network
6%
Predictive Classification
6%
Sampling Methods
6%
Speech Enhancement
5%
Transformation Parameters
5%
Unlabeled Data
5%
I-vector
5%
Prior Density
5%
Speech Separation
5%
Large Language Models
5%
Linear Regression
5%
Model Selection
5%
Acoustic Features
5%
