Chiori Hori

- Phone: 617-621-7568
- Email:
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Position:
Research / Technical Staff
Senior Principal Research Scientist -
Education:
Ph.D., Tokyo Institute of Technology, 2002 -
Research Areas:
External Links:
Chiori's Quick Links
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Biography
Chiori has been a member of MERL's research team since 2015. Her work is focused on spoken dialog and audio visual scene-aware dialog technologies toward human-robot communications. She's on the editorial board of "Computer Speech and Language" and is a technical committee member of "Speech and Language Processing Group" of IEEE Signal Processing Society. Prior to joining MERL, Chiori spent 8 years at Japan's National Institute of Information and Communication Technology (NICT), where she held the position of Research Manager of the Spoken Language Communication Laboratory. She also spent time researching at Carnegie Mellon and the NTT Communication Science Laboratories, prior to NICT.
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Recent News & Events
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NEWS MERL's Scene-Aware Interaction Technology Featured in Mitsubishi Electric Corporation Press Release Date: July 22, 2020
Where: Tokyo, Japan
MERL Contacts: Anoop Cherian; Bret Harsham; Chiori Hori; Takaaki Hori; Jonathan Le Roux; Tim Marks; Alan Sullivan; Anthony Vetro
Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Speech & AudioBrief- Mitsubishi Electric Corporation announced that the company has developed what it believes to be the world’s first technology capable of highly natural and intuitive interaction with humans based on a scene-aware capability to translate multimodal sensing information into natural language.
The novel technology, Scene-Aware Interaction, incorporates Mitsubishi Electric’s proprietary Maisart® compact AI technology to analyze multimodal sensing information for highly natural and intuitive interaction with humans through context-dependent generation of natural language. The technology recognizes contextual objects and events based on multimodal sensing information, such as images and video captured with cameras, audio information recorded with microphones, and localization information measured with LiDAR.
Scene-Aware Interaction for car navigation, one target application, will provide drivers with intuitive route guidance. The technology is also expected to have applicability to human-machine interfaces for in-vehicle infotainment, interaction with service robots in building and factory automation systems, systems that monitor the health and well-being of people, surveillance systems that interpret complex scenes for humans and encourage social distancing, support for touchless operation of equipment in public areas, and much more. The technology is based on recent research by MERL's Speech & Audio and Computer Vision groups.
Demonstration Video:
Link:
Mitsubishi Electric Corporation Press Release
- Mitsubishi Electric Corporation announced that the company has developed what it believes to be the world’s first technology capable of highly natural and intuitive interaction with humans based on a scene-aware capability to translate multimodal sensing information into natural language.
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NEWS MERL presenting 13 papers and an industry talk at ICASSP 2020 Date: May 4, 2020 - May 8, 2020
Where: Virtual Barcelona
MERL Contacts: Karl Berntorp; Petros Boufounos; Chiori Hori; Takaaki Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Yanting Ma; Hassan Mansour; Niko Moritz; Philip Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & AudioBrief- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.
Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, array processing, and parameter estimation. Videos for all talks are available on MERL's YouTube channel, with corresponding links in the references below.
This year again, MERL is a sponsor of the conference and will be participating in the Student Job Fair; please join us to learn about our internship program and career opportunities.
ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year. Originally planned to be held in Barcelona, Spain, ICASSP has moved to a fully virtual setting due to the COVID-19 crisis, with free registration for participants not covering a paper.
- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.
See All News & Events for Chiori -
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Research Highlights
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MERL Publications
- "Transformer-based Long-context End-to-end Speech Recognition", Annual Conference of the International Speech Communication Association (Interspeech), DOI: 10.21437/Interspeech.2020-2928, October 2020, pp. 5011-5015.BibTeX TR2020-139 PDF
- @inproceedings{Hori2020oct,
- author = {Hori, Takaaki and Moritz, Niko and Hori, Chiori and Le Roux, Jonathan},
- title = {Transformer-based Long-context End-to-end Speech Recognition},
- booktitle = {Annual Conference of the International Speech Communication Association (Interspeech)},
- year = 2020,
- pages = {5011--5015},
- month = oct,
- doi = {10.21437/Interspeech.2020-2928},
- issn = {1990-9772},
- url = {https://www.merl.com/publications/TR2020-139}
- }
, - "Multi-Pass Transformer for Machine Translation", arXiv, September 2020. ,
- "Spatio-Temporal Scene Graphs for Video Dialo", arXiv, July 2020. ,
- "Multi-Layer Content Interaction Through Quaternion Product For Visual Question Answering", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053595, April 2020, pp. 4412-4416.BibTeX TR2020-046 PDF
- @inproceedings{Shi2020apr,
- author = {Shi, Lei and Geng, Shijie and Shuang, Kai and Hori, Chiori and Liu, Songxiang and Gao, Peng and Su, Sen},
- title = {Multi-Layer Content Interaction Through Quaternion Product For Visual Question Answering},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2020,
- pages = {4412--4416},
- month = apr,
- publisher = {IEEE},
- doi = {10.1109/ICASSP40776.2020.9053595},
- issn = {2379-190X},
- isbn = {978-1-5090-6631-5},
- url = {https://www.merl.com/publications/TR2020-046}
- }
, - "Overview of the seventh Dialog System Technology Challenge: DSTC7", Computer Speech and Language, DOI: 10.1016/j.csl.2020.101068, Vol. 62, March 2020.BibTeX TR2020-029 PDF
- @article{D’Haro2020mar,
- author = {D’Haro, Luis, Fernando and Yoshino, Koichiro and Hori, Chiori and Marks, Tim and Polymenakos, Lazaros and Kummerfeld, Jonathan, k. and Galley, Michel and Gao, Xiang},
- title = {Overview of the seventh Dialog System Technology Challenge: DSTC7},
- journal = {Computer Speech and Language},
- year = 2020,
- volume = 62,
- month = mar,
- doi = {10.1016/j.csl.2020.101068},
- url = {https://www.merl.com/publications/TR2020-029}
- }
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- "Transformer-based Long-context End-to-end Speech Recognition", Annual Conference of the International Speech Communication Association (Interspeech), DOI: 10.21437/Interspeech.2020-2928, October 2020, pp. 5011-5015.
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MERL Issued Patents
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Title: "Method and System for Multi-Modal Fusion Model"
Inventors: Hori, Chiori; Hori, Takaaki; Hershey, John R.; Marks, Tim
Patent No.: 10,417,498
Issue Date: Sep 17, 2019 -
Title: "Method and System for Training Language Models to Reduce Recognition Errors"
Inventors: Hori, Takaaki; Hori, Chiori; Watanabe, Shinji; Hershey, John R.
Patent No.: 10,176,799
Issue Date: Jan 8, 2019 -
Title: "Method and System for Role Dependent Context Sensitive Spoken and Textual Language Understanding with Neural Networks"
Inventors: Hori, Chiori; Hori, Takaaki; Watanabe, Shinji; Hershey, John R.
Patent No.: 9,842,106
Issue Date: Dec 12, 2017
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Title: "Method and System for Multi-Modal Fusion Model"