咨询与建议

限定检索结果

文献类型

  • 76 篇 会议
  • 62 篇 期刊文献
  • 1 篇 学位论文

馆藏范围

  • 139 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 135 篇 工学
    • 94 篇 计算机科学与技术...
    • 51 篇 电气工程
    • 22 篇 信息与通信工程
    • 18 篇 软件工程
    • 14 篇 控制科学与工程
    • 9 篇 交通运输工程
    • 6 篇 石油与天然气工程
    • 5 篇 测绘科学与技术
    • 4 篇 动力工程及工程热...
    • 4 篇 土木工程
    • 2 篇 机械工程
    • 2 篇 电子科学与技术(可...
    • 2 篇 船舶与海洋工程
    • 2 篇 生物医学工程(可授...
    • 2 篇 安全科学与工程
    • 1 篇 光学工程
  • 28 篇 理学
    • 19 篇 物理学
    • 3 篇 地球物理学
    • 2 篇 数学
    • 2 篇 化学
    • 1 篇 地理学
    • 1 篇 大气科学
    • 1 篇 海洋科学
  • 23 篇 医学
    • 19 篇 临床医学
    • 3 篇 基础医学(可授医学...
  • 9 篇 管理学
    • 9 篇 管理科学与工程(可...
    • 2 篇 图书情报与档案管...
  • 2 篇 文学
    • 2 篇 外国语言文学
  • 1 篇 经济学
    • 1 篇 理论经济学
  • 1 篇 教育学
    • 1 篇 教育学

主题

  • 139 篇 sequence-to-sequ...
  • 18 篇 deep learning
  • 17 篇 attention mechan...
  • 12 篇 speech synthesis
  • 10 篇 natural language...
  • 8 篇 speech recogniti...
  • 7 篇 transformer
  • 7 篇 attention
  • 6 篇 training
  • 5 篇 transformers
  • 5 篇 decoding
  • 5 篇 feature extracti...
  • 4 篇 semantic segment...
  • 4 篇 transfer learnin...
  • 4 篇 machine learning
  • 4 篇 text-to-speech s...
  • 4 篇 neural machine t...
  • 3 篇 machine translat...
  • 3 篇 automated progra...
  • 3 篇 lstm

机构

  • 3 篇 google mountain ...
  • 3 篇 google llc mount...
  • 2 篇 google res mount...
  • 2 篇 soongsil univ de...
  • 2 篇 nara inst sci & ...
  • 2 篇 soongsil univ sc...
  • 2 篇 nagoya univ info...
  • 2 篇 natl inst inform...
  • 2 篇 univ trento dept...
  • 2 篇 cent china norma...
  • 2 篇 south china univ...
  • 2 篇 fdn bruno kessle...
  • 1 篇 columbia univers...
  • 1 篇 indian inst trop...
  • 1 篇 fdn bruno kessle...
  • 1 篇 city univ hong k...
  • 1 篇 chung ang univ g...
  • 1 篇 jd intelligent c...
  • 1 篇 shandong enginee...
  • 1 篇 ping an technol ...

作者

  • 4 篇 jia ye
  • 4 篇 weiss ron j.
  • 4 篇 bovolo francesca
  • 4 篇 ghosh raktim
  • 4 篇 biadsy fadi
  • 3 篇 moreno pedro j.
  • 3 篇 wu yonghui
  • 2 篇 yamagishi junich...
  • 2 篇 johnson melvin
  • 2 篇 chen youzheng
  • 2 篇 tan xiaoyu
  • 2 篇 ramabhadran bhuv...
  • 2 篇 nakamura satoshi
  • 2 篇 jiang liyang
  • 2 篇 li min
  • 2 篇 lee soowon
  • 2 篇 okamoto takuma
  • 2 篇 kawahara tatsuya
  • 2 篇 wu chung-hsien
  • 2 篇 doshi rohan

语言

  • 138 篇 英文
  • 1 篇 德文
  • 1 篇 法文
检索条件"主题词=sequence-to-sequence Model"
139 条 记 录,以下是91-100 订阅
排序:
Context- and sequence-Aware Convolutional Recurrent Encoder for Neural Machine Translation  21
Context- and Sequence-Aware Convolutional Recurrent Encoder ...
收藏 引用
36th Annual ACM Symposium on Applied Computing (SAC)
作者: Mallick, Ritam Susan, Seba Agrawal, Vaibhaw Garg, Rizul Rawal, Prateek Delhi Technol Univ Rohini Delhi 12 India
Neural Machine Translation(1) model is a sequence-to-sequence converter based on neural networks. Existing models use recurrent neural networks to construct both the encoder and decoder modules. In alternative researc... 详细信息
来源: 评论
High Quality Streaming Speech Synthesis with Low, Sentence-Length-Independent Latency  21
High Quality Streaming Speech Synthesis with Low, Sentence-L...
收藏 引用
Interspeech Conference
作者: Ellinas, Nikolaos Vamvoukakis, Georgios Markopoulos, Konstantinos Chalamandaris, Aimilios Maniati, Georgia Kakoulidis, Panos Raptis, Spyros Sung, June Sig Park, Hyoungmin Tsiakoulis, Pirros Samsung Elect Innoet Attica Greece Samsung Elect Mobile Commun Business Suwon Gyeonggi Do South Korea
This paper presents an end-to-end text-to-speech system with low latency on a CPU, suitable for real-time applications. The system is composed of an autoregressive attention-based sequence-to-sequence acoustic model a... 详细信息
来源: 评论
Personalized Dialogue Response Generation Learned from Monologues  20
Personalized Dialogue Response Generation Learned from Monol...
收藏 引用
Interspeech Conference
作者: Su, Feng-Guang Hsu, Aliyah R. Tuan, Yi-Lin Lee, Hung-Yi Natl Taiwan Univ Dept Elect Engn Taipei Taiwan
Personalized responses are essential for having an informative and human-like conversation. Because it is difficult to collect a large amount of dialogues involved with specific speakers, it is desirable that chatbot ... 详细信息
来源: 评论
LEVERAGING WEAKLY SUPERVISED DATA TO IMPROVE END-TO-END SPEECH-TO-TEXT TRANSLATION  44
LEVERAGING WEAKLY SUPERVISED DATA TO IMPROVE END-TO-END SPEE...
收藏 引用
44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Jia, Ye Johnson, Melvin Macherey, Wolfgang Weiss, Ron J. Cao, Yuan Chiu, Chung-Cheng Ari, Naveen Laurenzo, Stella Wu, Yonghui Google Res Mountain View CA 94043 USA
End-to-end Speech Translation (ST) models have many potential advantages when compared to the cascade of Automatic Speech Recognition (ASR) and text Machine Translation (MT) models, including lowered inference latency... 详细信息
来源: 评论
Nonintrusive Load Monitoring Based on Deep Learning  1
收藏 引用
6th ECML PKDD International Workshop on Data Analytics for Renewable Energy Integration (DARE)
作者: Wang, Ke Zhong, Haiwang Yu, Nanpeng Xia, Qing Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Tsinghua Univ State Key Lab Control & Simulat Power Syst & Gene Beijing 100084 Peoples R China Univ Calif Riverside Riverside CA 92521 USA
This paper presents a novel nonintrusive load monitoring method based on deep learning. Unlike the existing work based on convolutional neural network and recurrent neural network with fully connected layers, this pap... 详细信息
来源: 评论
MTrajRec: Map-Constrained Trajectory Recovery via Seq2Seq Multi-task Learning  21
MTrajRec: Map-Constrained Trajectory Recovery via Seq2Seq Mu...
收藏 引用
27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
作者: Ren, Huimin Ruan, Sijie Li, Yanhua Bao, Jie Meng, Chuishi Li, Ruiyuan Zheng, Yu Worcester Polytech Inst Worcester MA 01609 USA Xidian Univ Xian Shaanxi Peoples R China Chongqing Univ Chongqing Peoples R China JD Intelligent Cities Res Beijing Peoples R China
With the increasing adoption of GPS modules, there are a wide range of urban applications based on trajectory data analysis, such as vehicle navigation, travel time estimation, and driver behavior analysis. The effect... 详细信息
来源: 评论
Attention model for articulatory features detection  20
Attention model for articulatory features detection
收藏 引用
Interspeech Conference
作者: Karaulov, Ievgen Tkanov, Dmytro Sciforce Kharkiv Ukraine
Articulatory distinctive features, as well as phonetic transcription, play important role in speech-related tasks: computer-assisted pronunciation training, text-to-speech conversion (TTS), studying speech production ... 详细信息
来源: 评论
Triple M: A Practical Text-to-speech Synthesis System With Multi-guidance Attention And Multi-band Multi-time LPCNet  22
Triple M: A Practical Text-to-speech Synthesis System With M...
收藏 引用
Interspeech Conference
作者: Lin, Shilun Xie, Fenglong Meng, Li Li, Xinhui Lu, Li Tencent Beijing Peoples R China
In this work, a robust and efficient text-to-speech (TTS) synthesis system named Triple M is proposed for large-scale online application. The key components of Triple M are: 1) A sequence-to-sequence model adopts a no... 详细信息
来源: 评论
TRANSFORMER-BASED TEXT-TO-SPEECH WITH WEIGHTED FORCED ATTENTION
TRANSFORMER-BASED TEXT-TO-SPEECH WITH WEIGHTED FORCED ATTENT...
收藏 引用
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Okamoto, Takuma Toda, Tomoki Shiga, Yoshinori Kawai, Hisashi Natl Inst Informat & Commun Technol Tokyo Japan Nagoya Univ Informat Technol Ctr Nagoya Aichi Japan
This paper investigates state-of-the-art Transformer- and FastSpeech-based high-fidelity neural text-to-speech (TTS) with full-context label input for pitch accent languages. The aim is to realize faster training than... 详细信息
来源: 评论
FORWARD ATTENTION IN sequence-TO-sequence ACOUSTIC modelING FOR SPEECH SYNTHESIS
FORWARD ATTENTION IN SEQUENCE-TO-SEQUENCE ACOUSTIC MODELING ...
收藏 引用
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Zhang, Jing-Xuan Ling, Zhen-Hua Dai, Li-Rong Univ Sci & Technol China Natl Engn Lab Speech & Language Informat Proc Hefei Anhui Peoples R China
This paper proposes a forward attention method for the sequence-to-sequence acoustic modeling of speech synthesis. This method is motivated by the nature of the monotonic alignment from phone sequences to acoustic seq... 详细信息
来源: 评论