公开(公告)号：EP3245652B1

公开(公告)日：2019-07-10

申请号：EP16869294.5

申请日：2016-11-23

申请人： Baidu USA LLC

发明人： CATANZARO, Bryan ,  CHEN, Jingdong ,  CHRZANOWSKI, Mike ,  ELSEN, Erich ,  ENGEL, Jesse ,  FOUGNER, Christopher ,  HAN, Xu ,  HANNUN, Awni ,  PRENGER, Ryan ,  SATHEESH, Sanjeev ,  SENGUPTA, Shubhabrata ,  YOGATAMA, Dani ,  WANG, Chong ,  ZHAN, Jun ,  ZHU, Zhenyao ,  AMODEI, Dario

IPC分类号： G10L15/16 ,  G10L15/06 ,  G10L15/08 ,  G10L15/183

公开(公告)号：EP3245597A1

公开(公告)日：2017-11-22

申请号：EP16869302.6

申请日：2016-11-23

申请人： Baidu USA LLC

发明人： CATANZARO, Bryan ,  CHEN, Jingdong ,  CHRZANOWSKI, Mike ,  ELSEN, Erich ,  ENGEL, Jesse ,  FOUGNER, Christopher ,  HAN, Xu ,  HANNUN, Awni ,  PRENGER, Ryan ,  SATHEESH, Sanjeev ,  SENGUPTA, Shubhabrata ,  YOGATAMA, Dani ,  WANG, Chong ,  ZHAN, Jun ,  ZHU, Zhenyao ,  AMODEI, Dario

IPC分类号： G06F17/28 ,  G10L15/04 ,  G10L15/06 ,  G10L15/08 ,  G10L15/183 ,  G10L15/28

摘要： Embodiments of end-to-end deep learning systems and methods are disclosed to recognize speech of vastly different languages, such as English or Mandarin Chinese. In embodiments, the entire pipelines of hand-engineered components are replaced with neural networks, and the end-to-end learning allows handling a diverse variety of speech including noisy environments, accents, and different languages. Using a trained embodiment and an embodiment of a batch dispatch technique with GPUs in a data center, an end-to-end deep learning system can be inexpensively deployed in an online setting, delivering low latency when serving users at scale.

公开(公告)号：EP3245597B1

公开(公告)日：2020-08-26

申请号：EP16869302.6

申请日：2016-11-23

申请人： Baidu USA LLC

发明人： CATANZARO, Bryan ,  CHEN, Jingdong ,  CHRZANOWSKI, Mike ,  ELSEN, Erich ,  ENGEL, Jesse ,  FOUGNER, Christopher ,  HAN, Xu ,  HANNUN, Awni ,  PRENGER, Ryan ,  SATHEESH, Sanjeev ,  SENGUPTA, Shubhabrata ,  YOGATAMA, Dani ,  WANG, Chong ,  ZHAN, Jun ,  ZHU, Zhenyao ,  AMODEI, Dario

IPC分类号： G10L15/14 ,  G10L15/16 ,  G10L15/183 ,  G06F40/40

公开(公告)号：EP3245652A1

公开(公告)日：2017-11-22

申请号：EP16869294.5

申请日：2016-11-23

申请人： Baidu USA LLC

发明人： CATANZARO, Bryan ,  CHEN, Jingdong ,  CHRZANOWSKI, Mike ,  ELSEN, Erich ,  ENGEL, Jesse ,  FOUGNER, Christopher ,  HAN, Xu ,  HANNUN, Awni ,  PRENGER, Ryan ,  SATHEESH, Sanjeev ,  SENGUPTA, Shubhabrata ,  YOGATAMA, Dani ,  WANG, Chong ,  ZHAN, Jun ,  ZHU, Zhenyao ,  AMODEI, Dario

IPC分类号： G10L15/16 ,  G10L15/06 ,  G10L15/08 ,  G10L15/183

CPC分类号： G10L15/16 ,  G06N3/0445 ,  G06N3/084 ,  G10L15/02 ,  G10L15/063 ,  G10L15/14 ,  G10L15/183 ,  G10L15/197 ,  G10L25/18 ,  G10L25/21 ,  G10L2015/0635

摘要： Embodiments of end-to-end deep learning systems and methods are disclosed to recognize speech of vastly different languages, such as English or Mandarin Chinese. In embodiments, the entire pipelines of hand-engineered components are replaced with neural networks, and the end-to-end learning allows handling a diverse variety of speech including noisy environments, accents, and different languages. Using a trained embodiment and an embodiment of a batch dispatch technique with GPUs in a data center, an end-to-end deep learning system can be inexpensively deployed in an online setting, delivering low latency when serving users at scale.