《Autoencoder-based Semi-Supervised Curriculum Learning For Out-of-domain Speaker Verification》电子版地址

简介: Autoencoder-based Semi-Supervised Curriculum Learning For Out-of-domain Speaker Verification

《Autoencoder-based Semi-Supervised Curriculum Learning For Out-of-domain Speaker Verification》Autoencoder-based Semi-Supervised Curriculum Learning For Out-of-domain Speaker Verification

电子书:

屏幕快照 2022-06-17 上午9.58.35.png

                
            </div>
目录
相关文章
|
数据挖掘
【提示学习】Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification
文章提出了一种简单确高效地构建verbalization的方法:
|
机器学习/深度学习 人工智能 自然语言处理
OneIE:A Joint Neural Model for Information Extraction with Global Features论文解读
大多数现有的用于信息抽取(IE)的联合神经网络模型使用局部任务特定的分类器来预测单个实例(例如,触发词,关系)的标签,而不管它们之间的交互。
181 0
|
自然语言处理
【论文速递】ACL 2022 - Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extr
在本文中,我们提出了一个既有效又高效的模型PAIE,用于句子级和文档级的事件论元抽取(EAE),即使在缺乏训练数据的情况下也能很好地泛化。一方面,PAIE利用抽取目标的提示调优,以充分利用预训练语言模型(PLMs)的优势。
83 0
|
机器学习/深度学习 自然语言处理 算法
Joint Information Extraction with Cross-Task and Cross-Instance High-Order Modeling 论文解读
先前的信息抽取(IE)工作通常独立地预测不同的任务和实例(例如,事件触发词、实体、角色、关系),而忽略了它们的相互作用,导致模型效率低下。
95 0
|
机器学习/深度学习 编解码 数据可视化
Speech Emotion Recognition With Local-Global aware Deep Representation Learning论文解读
语音情感识别(SER)通过从语音信号中推断人的情绪和情感状态,在改善人与机器之间的交互方面发挥着至关重要的作用。尽管最近的工作主要集中于从手工制作的特征中挖掘时空信息,但我们探索如何从动态时间尺度中建模语音情绪的时间模式。
140 0
|
机器学习/深度学习 算法 数据挖掘
【多标签文本分类】Improved Neural Network-based Multi-label Classification with Better Initialization ……
【多标签文本分类】Improved Neural Network-based Multi-label Classification with Better Initialization ……
127 0
【多标签文本分类】Improved Neural Network-based Multi-label Classification with Better Initialization ……
|
机器学习/深度学习 传感器 编解码
Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supe
Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supe
98 0
Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supe
《Multi-Task Multi-Network Joint-Learning of Deep Residual Networks and Cycle-Consistency Generative Adversarial Networks for Robust Speech Recognition》电子版地址
Multi-Task Multi-Network Joint-Learning of Deep Residual Networks and Cycle-Consistency Generative Adversarial Networks for Robust Speech Recognition
104 0
《Multi-Task Multi-Network Joint-Learning of Deep Residual Networks and Cycle-Consistency Generative Adversarial Networks for Robust Speech Recognition》电子版地址
《Investigation of Transformer based Spelling Correction Model for CTC-based End-to-End Mandarin Speech Recognition》电子版地址
Investigation of Transformer based Spelling Correction Model for CTC-based End-to-End Mandarin Speech Recognition
95 0
《Investigation of Transformer based Spelling Correction Model for CTC-based End-to-End Mandarin Speech Recognition》电子版地址
|
搜索推荐 PyTorch 算法框架/工具
Re30:读论文 LegalGNN: Legal Information Enhanced Graph Neural Network for Recommendation
Re30:读论文 LegalGNN: Legal Information Enhanced Graph Neural Network for Recommendation
Re30:读论文 LegalGNN: Legal Information Enhanced Graph Neural Network for Recommendation