Related papers: Miutsu: NTU's TaskBot for the Alexa Prize
Effective task management is essential to successful team collaboration. While the past decade has seen considerable innovation in systems that track and manage group tasks, these innovations have typically been outside of the principal…
This paper describes our dialogue system submitted to Dialogue Robot Competition 2023. The system's task is to help a user at a travel agency decide on a plan for visiting two sightseeing spots in Kyoto City that satisfy the user. Our…
Learning by Asking (LBA) enables robots to identify knowledge gaps during task execution and acquire the missing information by asking targeted questions. However, different tasks often require different types of questions, and how to adapt…
Audio-visual learning seeks to enhance the computer's multi-modal perception leveraging the correlation between the auditory and visual modalities. Despite their many useful downstream tasks, such as video retrieval, AR/VR, and…
Large Language Models (LLM) are increasingly being explored for problem-solving tasks. However, their strategic planning capability is often viewed with skepticism. Recent studies have incorporated the Monte Carlo Tree Search (MCTS)…
This paper describes Team Delft's robot, which won the Amazon Picking Challenge 2016, including both the Picking and the Stowing competitions. The goal of the challenge is to automate pick and place operations in unstructured environments,…
We introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. jiant enables modular and configuration-driven experimentation with state-of-the-art models and implements a broad…
We report on the design and development of the CASPR system, a socialbot designed to compete in the Amazon Alexa Socialbot Challenge 4. CASPR's distinguishing characteristic is that it will use automated commonsense reasoning to truly…
Large transformer models can highly improve Answer Sentence Selection (AS2) tasks, but their high computational costs prevent their use in many real-world applications. In this paper, we explore the following research question: How can we…
End-to-end Task-oriented Dialogue Systems (TDSs) have attracted a lot of attention for their superiority (e.g., in terms of global optimization) over pipeline modularized TDSs. Previous studies on end-to-end TDSs use a single-module model…
We envision robots that can collaborate and communicate seamlessly with humans. It is necessary for such robots to decide both what to say and how to act, while interacting with humans. To this end, we introduce a new task, dialogue object…
Task-oriented dialogue (ToD) systems help users execute well-defined tasks across a variety of domains (e.g., $\textit{flight booking}$ or $\textit{food ordering}$), with their Natural Language Understanding (NLU) components being dedicated…
Training a spoken language understanding system, as the one in Alexa, typically requires a large human-annotated corpus of data. Manual annotations are expensive and time consuming. In Alexa Skill Kit (ASK) user experience with the skill…
Service robots for personal use in the home and the workplace require end-user development solutions for swiftly scripting robot tasks as the need arises. Many existing solutions preserve ease, efficiency, and convenience through simple…
This paper describes our dialogue robot system, OSbot, developed for Dialogue Robot Competition 2022. The dialogue flow is based on state transitions described manually and the transition conditions use the results of keyword extraction and…
This paper describes the dialog robot system designed by Team Irisapu for the preliminary round of the Dialogue Robot Competition 2023 (DRC2023). In order to generate dialogue responses flexibly while adhering to predetermined scenarios, we…
We consider the problem of building an assistive robotic system that can help humans in daily household cleanup tasks. Creating such an autonomous system in real-world environments is inherently quite challenging, as a general solution may…
Information-seeking AI assistant systems aim to answer users' queries about knowledge in a timely manner. However, both the human-perceived helpfulness of information-seeking assistant systems and its fairness implication are…
Tables and table-based use cases play a crucial role in many important real-world applications, such as spreadsheets, databases, and computational notebooks, which traditionally require expert-level users like data engineers, data analysts,…
This paper investigates the implementation of voice-enabled Google Assistant and Amazon Alexa on Raspberry Pi. Virtual Assistants are being a new trend in how we interact or do computations with physical devices. A voice-enabled system…