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Conversation Agents for Urban Navigation

Implementing Organization

Indian Institute of Technology (IIT)
Principal Investigator
Dr Balaraman Ravindran
Professor
|
Indian Institute of Technology (IIT)
CO-Principal Investigator
Dr Pawan Goyal
Associate Professor
CO-Principal Investigator
Dr Gitakrishnan Ramadurai
Associate Professor
|
Indian Institute of Technology (IIT)
CO-Principal Investigator
Dr Niloy Ganguly
Professor
|
Indian Institute of Technology (IIT) Kharagpur
CO-Principal Investigator
Dr Partha Pratim Talukdar
Staff Research Scientist
|
Indian Institute of Science

About

In the Indian context, one of the crucial requirements is to have an automatic travel assistant, that can assist the commuters and tourists in planning their travel as well as obtaining recommendations. This would include use cases such as: (1) A villager trying to find a way around in a city, local language support becomes essential (2) English-speaking city dweller, but needs to work around civic constructions, road blockages in the city (3) for law-enforcement agents to get real-time info about various traffic situations and bottlenecks. The disruptions can be either pre-announced (known to law-enforcement agency) or it may be sudden (can again be gathered from social networks). Increasingly ride-sharing is emerging as an economical but private way to drive. One of the main impediments behind ride-sharing is the apprehension commuters have about sharing space with strangers. With the support of background social networks which generate real-time information, the agent can provide a pleasurable social environment for ride-sharing. Summing up, the information upon which chatbots will act will come from first a slow-changing database that stores information about specific routes, sites as well as ratings of people. This would be supplemented with more real-time unstructured information – an important task would be to structure them and make them useful. This would be possible if we can build up domain-specific knowledge graphs. It is aimed to build a neural conversational system, which is assisted by domain knowledge, in the form of a knowledge graph. Another important aspect of the Chabot is its ability to interact with the subject in regional languages. In order to have the interface as natural as possible, investigators plan to make it operational in two regional languages (Hindi, Bengali) as well as its corresponding code-mixing version. The entire solution will be deployed within a city and extensive experimentations would be done to understand the various nuances attached

Achievements

Produced many high-impact publications from this work that have appeared in some of the top conferences in the world.

Industry Collaboration

Intel Technology India Pvt Ltd, Bangalore
Funding Organization
Funding Organization
Department of Science and Technology (DST)
Ministry of Education (MoE)
Quick Information
Area of Research
Computer Sciences and Information Technology
Focus Area
Urban Navigation
Start Year
2019
Sanction Amount
₹ 68.20 L
Status
Ongoing
Contact
ravi@cse.iitm.ac.in ; pawang@cse.iitkgp.ac.in
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
00
No. of Patents
Filed : 00
Grant : 00
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