BEGIN:VCALENDAR VERSION:2.0 PRODID:-//128.220.36.25//NONSGML kigkonsult.se iCalcreator 2.26.9// CALSCALE:GREGORIAN METHOD:PUBLISH X-FROM-URL:https://www.clsp.jhu.edu X-WR-TIMEZONE:America/New_York BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:STANDARD DTSTART:20231105T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RDATE:20241103T020000 TZNAME:EST END:STANDARD BEGIN:DAYLIGHT DTSTART:20240310T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RDATE:20250309T020000 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:ai1ec-20120@www.clsp.jhu.edu DTSTAMP:20240328T120122Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:Abstract\nRobotics@Google’s mission is to make robots useful in the real world through machine learning. We are excited about a new model for robotics\, designed for generalization across diverse environments an d instructions. This model is focused on scalable data-driven learning\, w hich is task-agnostic\, leverages simulation\, learns from past experience \, and can be quickly adapted to work in the real-world through limited in teractions. In this talk\, we’ll share some of our recent work in this dir ection in both manipulation and locomotion applications.\nBiography\nCarol ina Parada is a Senior Engineering Manager at Google Robotics. She leads t he robot-mobility group\, which focuses on improving robot motion planning \, navigation\, and locomotion\, using reinforcement learning. Prior to th at\, she led the camera perception team for self-driving cars at Nvidia fo r 2 years. She was also a lead with Speech @ Google for 7 years\, where sh e drove multiple research and engineering efforts that enabled Ok Google\, the Google Assistant\, and Voice-Search. Carolina grew up in Venezuela an d moved to the US to pursue a B.S. and M.S. degree in Electrical Engineeri ng at University of Washington and her Phd at Johns Hopkins University at the Center for Language and Speech Processing (CLSP). DTSTART;TZID=America/New_York:20210423T120000 DTEND;TZID=America/New_York:20210423T131500 LOCATION:via Zoom SEQUENCE:0 SUMMARY:Carolina Parada (Google AI) “State of Robotics @ Google” URL:https://www.clsp.jhu.edu/events/carolina-parada-google-ai/ X-COST-TYPE:free X-ALT-DESC;FMTTYPE=text/html:\\n\\n
\\nAbstr act
\nRobotics@Google’s mission is to make robots useful i n the real world through machine learning. We are excited about a new mode l for robotics\, designed for generalization across diverse environments a nd instructions. This model is focused on scalable data-driven learning\, which is task-agnostic\, leverages simulation\, learns from past experienc e\, and can be quickly adapted to work in the real-world through limited i nteractions. In this talk\, we’ll share some of our recent work in this di rection in both manipulation and locomotion applications.
\n< strong>Biography
\nCarolina Parad a is a Senior Engineering Manager at Google Robotics. She leads the robot-mobility group\, which focuses on improving robot motion planning\, navigation\, and locomotion\, using reinforcement learning. Prior to that \, she led the camera perception team for self-driving cars at Nvidia for 2 years. She was also a lead with Speech @ Google for 7 years\, where she drove multiple research and engineering efforts that enabled Ok Google\, t he Google Assistant\, and Voice-Search. Carolina< /span> grew up in Venezuela and moved to the US to pursue a B.S. and M.S. degree in Electrical Engineering at University of Washington and her Phd a t Johns Hopkins University at the Center for Language and Speech Processin g (CLSP).
\n X-TAGS;LANGUAGE=en-US:2021\,April\,Parada END:VEVENT BEGIN:VEVENT UID:ai1ec-22403@www.clsp.jhu.edu DTSTAMP:20240328T120122Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:Abstract\nVoice conversion (VC) is a significant aspect of arti ficial intelligence. It is the study of how to convert one’s voice to soun d like that of another without changing the linguistic content. Voice conv ersion belongs to a general technical field of speech synthesis\, which co nverts text to speech or changes the properties of speech\, for example\, voice identity\, emotion\, and accents. Voice conversion involves multiple speech processing techniques\, such as speech analysis\, spectral convers ion\, prosody conversion\, speaker characterization\, and vocoding. With t he recent advances in theory and practice\, we are now able to produce hum an-like voice quality with high speaker similarity. In this talk\, Dr. Sis man will present the recent advances in voice conversion and discuss their promise and limitations. Dr. Sisman will also provide a summary of the av ailable resources for expressive voice conversion research.\nBiography\nDr . Berrak Sisman (Member\, IEEE) received the Ph.D. degree in electrical an d computer engineering from National University of Singapore in 2020\, ful ly funded by A*STAR Graduate Academy under Singapore International Graduat e Award (SINGA). She is currently working as a tenure-track Assistant Prof essor at the Erik Jonsson School Department of Electrical and Computer Eng ineering at University of Texas at Dallas\, United States. Prior to joinin g UT Dallas\, she was a faculty member at Singapore University of Technolo gy and Design (2020-2022). She was a Postdoctoral Research Fellow at the N ational University of Singapore (2019-2020). She was an exchange doctoral student at the University of Edinburgh and a visiting scholar at The Centr e for Speech Technology Research (CSTR)\, University of Edinburgh (2019). She was a visiting researcher at RIKEN Advanced Intelligence Project in Ja pan (2018). Her research is focused on machine learning\, signal processin g\, emotion\, speech synthesis and voice conversion.\nDr. Sisman has serve d as the Area Chair at INTERSPEECH 2021\, INTERSPEECH 2022\, IEEE SLT 2022 and as the Publication Chair at ICASSP 2022. She has been elected as a me mber of the IEEE Speech and Language Processing Technical Committee (SLTC) in the area of Speech Synthesis for the term from January 2022 to Decembe r 2024. She plays leadership roles in conference organizations and active in technical committees. She has served as the General Coordinator of the Student Advisory Committee (SAC) of International Speech Communication Ass ociation (ISCA). DTSTART;TZID=America/New_York:20221104T120000 DTEND;TZID=America/New_York:20221104T131500 LOCATION:Hackerman Hall B17 @ 3400 N. Charles Street\, Baltimore\, MD 21218 SEQUENCE:0 SUMMARY:Berrak Sisman (University of Texas at Dallas) “Speech Synthesis and Voice Conversion: Machine Learning can Mimic Anyone’s Voice” URL:https://www.clsp.jhu.edu/events/berrak-sisman-university-of-texas-at-da llas/ X-COST-TYPE:free X-ALT-DESC;FMTTYPE=text/html:\\n\\n\\nAbstr act
\nVoice conversion (VC) is a significant aspect of arti ficial intelligence. It is the study of how to convert one’s voice to soun d like that of another without changing the linguistic content. Voice conv ersion belongs to a general technical field of speech synthesis\, which co nverts text to speech or changes the properties of speech\, for example\, voice identity\, emotion\, and accents. Voice conversion involves multiple speech processing techniques\, such as speech analysis\, spectral convers ion\, prosody conversion\, speaker characterization\, and vocoding. With t he recent advances in theory and practice\, we are now able to produce hum an-like voice quality with high speaker similarity. In this talk\, Dr. Sis man will present the recent advances in voice conversion and discuss their promise and limitations. Dr. Sisman will also provide a summary of the av ailable resources for expressive voice conversion research.
\nDr. Berrak Sisman (Member\, IEEE) received th e Ph.D. degree in electrical and computer engineering from National Univer sity of Singapore in 2020\, fully funded by A*STAR Graduate Academy under Singapore International Graduate Award (SINGA). She is currently working a s a tenure-track Assistant Professor at the Erik Jonsson School Department of Electrical and Computer Engineering at University of Texas at Dallas\, United States. Prior to joining UT Dallas\, she was a faculty member at S ingapore University of Technology and Design (2020-2022). She was a Postdo ctoral Research Fellow at the National University of Singapore (2019-2020) . She was an exchange doctoral student at the University of Edinburgh and a visiting scholar at The Centre for Speech Technology Research (CSTR)\, U niversity of Edinburgh (2019). She was a visiting researcher at RIKEN Adva nced Intelligence Project in Japan (2018). Her research is focused on mach ine learning\, signal processing\, emotion\, speech synthesis and voice co nversion.
\nDr. Sisman has served as the Area Chair at INTERSPEECH 2 021\, INTERSPEECH 2022\, IEEE SLT 2022 and as the Publication Chair at ICA SSP 2022. She has been elected as a member of the IEEE Speech and Language Processing Technical Committee (SLTC) in the area of Speech Synthesis for the term from January 2022 to December 2024. She plays leadership roles i n conference organizations and active in technical committees. She has ser ved as the General Coordinator of the Student Advisory Committee (SAC) of International Speech Communication Association (ISCA).
\n X-TAGS;LANGUAGE=en-US:2022\,November\,Sisman END:VEVENT END:VCALENDAR