- Date: July 22, 2020
Where: Tokyo, Japan
MERL Contacts: Anoop Cherian; Chiori Hori; Jonathan Le Roux; Tim K. Marks; Anthony Vetro
Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Speech & Audio
Brief - 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.
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- Date: February 13, 2019
Where: Tokyo, Japan
MERL Contacts: Jonathan Le Roux; Gordon Wichern
Research Area: Speech & Audio
Brief - Mitsubishi Electric Corporation announced that it has developed the world's first technology capable of highly accurate multilingual speech recognition without being informed which language is being spoken. The novel technology, Seamless Speech Recognition, incorporates Mitsubishi Electric's proprietary Maisart compact AI technology and is built on a single system that can simultaneously identify and understand spoken languages. In tests involving 5 languages, the system achieved recognition with over 90 percent accuracy, without being informed which language was being spoken. When incorporating 5 more languages with lower resources, accuracy remained above 80 percent. The technology can also understand multiple people speaking either the same or different languages simultaneously. A live demonstration involving a multilingual airport guidance system took place on February 13 in Tokyo, Japan. It was widely covered by the Japanese media, with reports by all six main Japanese TV stations and multiple articles in print and online newspapers, including in Japan's top newspaper, Asahi Shimbun. The technology is based on recent research by MERL's Speech and Audio team.
Link:
Mitsubishi Electric Corporation Press Release
Media Coverage:
NHK, News (Japanese)
NHK World, News (English), video report (starting at 4'38")
TV Asahi, ANN news (Japanese)
Nippon TV, News24 (Japanese)
Fuji TV, Prime News Alpha (Japanese)
TV Tokyo, World Business Satellite (Japanese)
TV Tokyo, Morning Satellite (Japanese)
TBS, News, N Studio (Japanese)
The Asahi Shimbun (Japanese)
The Nikkei Shimbun (Japanese)
Nikkei xTech (Japanese)
Response (Japanese).
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- Date: Sunday, December 10, 2017
Location: Hyatt Regency, Long Beach, CA
MERL Contact: Chiori Hori
Research Area: Speech & Audio
Brief - MERL researcher Chiori Hori led the organization of the 6th edition of the Dialog System Technology Challenges (DSTC6). This year's edition of DSTC is split into three tracks: End-to-End Goal Oriented Dialog Learning, End-to-End Conversation Modeling, and Dialogue Breakdown Detection. A total of 23 teams from all over the world competed in the various tracks, and will meet at the Hyatt Regency in Long Beach, CA, USA on December 10 to present their results at a dedicated workshop colocated with NIPS 2017.
MERL's Speech and Audio Team and Mitsubishi Electric Corporation jointly submitted a set of systems to the End-to-End Conversation Modeling Track, obtaining the best rank among 19 submissions in terms of objective metrics.
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- Date: May 24, 2017
Where: Tokyo, Japan
MERL Contact: Jonathan Le Roux
Research Area: Speech & Audio
Brief - Mitsubishi Electric Corporation announced that it has created the world's first technology that separates in real time the simultaneous speech of multiple unknown speakers recorded with a single microphone. It's a key step towards building machines that can interact in noisy environments, in the same way that humans can have meaningful conversations in the presence of many other conversations. In tests, the simultaneous speeches of two and three people were separated with up to 90 and 80 percent accuracy, respectively. The novel technology, which was realized with Mitsubishi Electric's proprietary "Deep Clustering" method based on artificial intelligence (AI), is expected to contribute to more intelligible voice communications and more accurate automatic speech recognition. A characteristic feature of this approach is its versatility, in the sense that voices can be separated regardless of their language or the gender of the speakers. A live speech separation demonstration that took place on May 24 in Tokyo, Japan, was widely covered by the Japanese media, with reports by three of the main Japanese TV stations and multiple articles in print and online newspapers. The technology is based on recent research by MERL's Speech and Audio team.
Links:
Mitsubishi Electric Corporation Press Release
MERL Deep Clustering Demo
Media Coverage:
Fuji TV, News, "Minna no Mirai" (Japanese)
The Nikkei (Japanese)
Nikkei Technology Online (Japanese)
Sankei Biz (Japanese)
EE Times Japan (Japanese)
ITpro (Japanese)
Nikkan Sports (Japanese)
Nikkan Kogyo Shimbun (Japanese)
Dempa Shimbun (Japanese)
Il Sole 24 Ore (Italian)
IEEE Spectrum (English).
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- Date: February 10, 2014
MERL Contacts: Jonathan Le Roux; Daniel N. Nikovski; Anthony Vetro Brief - Mitsubishi Electric Corporation demonstrated an ultra-simple HMI for in-car device operation using algorithms developed by MERL to predict user actions and destinations.
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- Date: October 22, 2012
Where: Annual Meeting of the Human Factors and Ergonomics Society (HFES)
Research Area: Speech & Audio
Brief - The paper "Evaluation of Two Types of In-Vehicle Music Retrieval and Navigation Systems" by Zhang, J., Borowsky, A., Schmidt-Nielsen, B., Harsham, B., Weinberg, G., Romoser, M.R.E. and Fisher, D.L. was presented at the Annual Meeting of the Human Factors and Ergonomics Society (HFES).
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- Date: November 30, 2011
Where: International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) Brief - The paper "Evaluating the Usability of a Head-Up Display for Selection from Choice Lists in Cars" by Weinberg, G., Harsham, B. and Medenica, Z. was presented at the International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI).
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- Date: June 27, 2011
Where: International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
Research Area: Speech & Audio
Brief - The paper "Investigating HUDs or the Presentation of Choice Lists in Car navigation Systems" by Weinberg, G., Harsham, B. and Medenica, Z. was presented at the International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design.
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- Date: September 7, 2010
Where: International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI)
Research Area: Speech & Audio
Brief - The paper "Contextual Push-to-talk: Shortening Voice Dialogs to Improve Driving Performance" by Weinberg, G., Harsham, B., Forlines, C. and Medenica, Z. was presented at the International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI).
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- Date: September 7, 2010
Where: Speech in Mobile and Pervasive Environments (SiMPE)
Research Area: Speech & Audio
Brief - The paper "Object-Oriented Multimodality for Safer-In-Vehicle Interfaces" by Weinberg, G. and Harsham, B. was presented at Speech in Mobile and Pervasive Environments (SiMPE).
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- Date: May 12, 2010
Where: Accident Analysis & Prevention
Research Area: Speech & Audio
Brief - The article "Evaluation of Different Speech and Touch Interfaces to In-vehicle Music Retrieval Systems" by Garay-Vega, L., Pradhan, A.K., Weinberg, G.L., Schmidt-Nielsen, B.K., Harsham, B.A., Shen, Y., Divekar, G., Romoser, M., Knodler, M. and Fisher, D.L. was published in Accident Analysis & Prevention.
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- Date: September 21, 2009
Where: International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI)
Research Area: Speech & Audio
Brief - The paper "Developing a Low-Cost Driving Simulator for the Evaluation of In-Vehicle Technologies" by Weinberg, G.L. and Harsham, B.A. was presented at the International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI).
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- Date: February 15, 2008
Where: Handbook of Research on User Interface Design and Evaluation for Mobile Technology
Research Area: Speech & Audio
Brief - The article "Speech-Based UI Design for the Automobile" by Schmidt-Nielsen, B., Harsham, B., Raj, B. and Forlines, C. was published in the book Handbook of Research on User Interface Design and Evaluation for Mobile Technology.
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- Date: October 23, 2005
Where: ACM Symposium on User Interface Software and Technology (UIST)
MERL Contact: William S. Yerazunis Brief - The papers "DTLens: Multi-user Tabletop Spatial Data Exploration" by Forlines, C. and Shen, C., "Zoom-and-Pick: Facilitating Visual Zooming and Precision Pointing with Interactive Handheld Projectors" by Forlines, C., Balakrishnan, R., Beardsley, P., van Baar, J. and Raskar, R. and "DT Controls: Adding Identity to Physical Interfaces" by Dietz, P.H., Harsham, B., Forlines, C., Leigh, D., Yerazunis, W., Shipman, S., Schmidt-Nielsen, B. and Ryall, K. were presented at the ACM Symposium on User Interface Software and Technology (UIST).
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