Life in Media Intelligence Laboratory

Media Intelligence Laboratory (Ogawa Laboratory) aims at developing fundamental technologies to operate pattern recognition systems in early stages (even when big-data are not available) and evolve them efficiently using accumulated data and their applications to smart maintenance and primary industry support (e.g., precision livestock farming and precision fisheries).

For that purpose, important problmes on acoustics and speech information processing, image and video information processing, pattern recognition, and machine learning have been studied and demonstrated in fields of the aforementioned social issues. Especially, we have focused on the following three viewpoints:

1. Robust Systems to Unknown Inputs: Let's develop pattern recognition algorithms that do not rely only on big-data by emulating human functions and behaviours.

2. Evolving Systems: Let's develop pattern recognition algorithms to adaptively evolve systems using accumulated data.

3. Explainable Systems: Let's develop pattern recognition algorithms that are explainable and intuitive to users.

A problem to be solved should not be limited to its application, and technologies applicable to various situations should be developed. For that purpose, our laboratory places an importance on explainable and intuitive researches i.e., incorporating ideas or thoughts to represent the target phenomena into models and algorithms.

Our laboratory has been managed in strong association with Perceptual Computing Laboratory (supervised by Prof. Tetsunori Kobayashi and Prof. Yoshihiko Hayashi) and collaborated with the following researchers:

• Prof. Tetsunori Kobayashi, Professor, Waseda University (Specialty: Perctptual Computing)

• Prof. Yoshihiko Hayashi, Professor, Waseda University (Specialty: Natural Language Processing)

• Dr. Yoichi Matsuyama, Associate Professor, Waseda University (Specialty: Conversational AI Media)

• Prof. Shinya Fujie, Associate Professor, Chiba Institute of Technology (Specialty: Dialog System, Conversation Robot, Kansei Engineering)

• Prof. Kazuya Ueki, Associate Professor, Meisei University (Specialty: Image and Video Processing)

• Dr. Teppei Nakano, Senior Researcher, Waseda University (Specialty: Software Engineering)

• Dr. Susumu Saito, Junior Researcher, Waseda University (Specialty: Crowdsourcing)

• Prof. Shinji Watanabe, Associate Professor, Carnegie Mellon University (Specialty: Speech and Language Processing)

• Dr. Jun Ogata, Team Leader of Intelligent Media Processing Research Team, The National Institute of Advanced Industrial Science and Technology (AIST) (Specialty: Spoken Language Processing, Time series processing)

• Prof. Hideitsu Hino, Professor, The Institute of Statistical Mathematics (Specialty: Mathematical Engineering)

• Prof. Minoru Sakaguchi, Professor, Kitasato University (Specialty: Veterinary Clinical Reproduction )

• Prof. Tomomi Sato, Professor, Yokohama City University (Specialty: Pediatric Nursing) 

Eventually, our group has worked on diverse research projects across acoustics, speech, image, video and language processing. An advantage is that students can learn many different research topics during their education.

We are sure that it is important for undergraduate students to realize how interesting researches are.

1st Semester

After the assignment of laboratory, problems with prospect of success will be presented by our laboratory. Students will choose an interesting problem. Through working on this, students can study research manners such as how to investigate literatures, how to use tools and softwares, how to arrange research outcomes, and so on. Students can work while keeping communication with graduate students.

2nd Semester

In 2nd semester, students can work on more advanced problems related to those done in 1st semester or start with working on other valuable problems proposed by themselves.

Most students are going to present their research outcomes in a domestic conference at the end of academic year and an international conference at the next academic year.

In the graduate school, students will be able to deeply understand and intuitively explain technologies by investigating research and development trends, and implementing and evaluating important, state-of-the-art technologies on acoustic and speech processing, image and video processing, natural language processing, pattern recognition, and machine learning. Especially, our laboratory places an importance on improving ability of discovering valuable research problems that have impact on many fields.

Students aim at presenting their research outcomes in one or more top international conferences and journal papers for each year.

See the details here (in Japanese).

• April: Welcome meeting, decision of research projects

• May: Spring camp (recreation)

• September: Summer camp (Interim research report and recreation)

• October: Computer Science Student Workshop

• December: Year-end party

• January: Presentation session of Bachelor's thesis and Master's thesis

• February: Defence of Bachelor's thesis and Master's thesis (Official)

• March: Graduation celemony

Survey Meeting for Graduate Students (Monday, Morning)

Graduate students report results of the literature survey to share information about technological trends and state-of-the-art technologies with all students.

Interim Research Report Meeting (Wednesday, Morning)

All students present their research progress for every two months. Since our group (i.e., Perceptual Computing and Media Intelligence Laboratory) has worked on diverse research projects, we place an importance on sharing information and discussions beyond research fields.

Pregress Report Group Meeting

All students share their research progress in detail and discuss deeply with professors and other students for each group.

• Speech and Pattern Recognition Group, supervised by Prof. Tetsuji Ogawa & Prof. Tetsunori Kobayashi (Monday, Afternoon)

• Dialogue Systems and Multiparty Conversation Group, supervised by Prof. Shinya Fujie & Prof. Tetsunori Kobayashi  (Tuesday, Afternoon)

• IoT Group, supervised by Dr. Teppei Nakano & Prof. Tetsuji Ogawa (Wednesday, Afternoon)

• Education Engineering Group, supervised by Dr. Yoichi Matsuyama & Prof. Tetsuji Ogawa (Thursday, Afternoon)

• Natural Language Processing Group, supervised by Prof. Yoshihiko Hayashi (Thursday, Afternoon)

Study Session on Machine Learning (Spring, Tuesday, Morning)

4th-year undergraduate students survey several important topics on pattern recognition and machine learning and share the information with other students. Graduate students can support with how to study and how to make presentations.