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Found 42 papers, 1 papers with code
Natural Language Processing for Computer Scientists and Data Scientists at a Large State University
The field of Natural Language Processing (NLP) changes rapidly, requiring course offerings to adjust with those changes, and NLP is not just for computer scientists; it’s a field that should be accessible to anyone who has a sufficient background.
Symbol and Communicative Grounding through Object Permanence with a Mobile Robot
Object permanence is the ability to form and recall mental representations of objects even when they are not in view.
Incremental Unit Networks for Multimodal, Fine-grained Information State Representation
We offer a fine-grained information state annotation scheme that follows directly from the Incremental Unit abstract model of dialogue processing when used within a multimodal, co-located, interactive setting.
Spellchecking for Children in Web Search: a Natural Language Interface Case-study
Given the more widespread nature of natural language interfaces, it is increasingly important to understand who are accessing those interfaces, and how those interfaces are being used.
Enriching Language Models with Visually-grounded Word Vectors and the Lancaster Sensorimotor Norms
Language models are trained only on text despite the fact that humans learn their first language in a highly interactive and multimodal environment where the first set of learned words are largely concrete, denoting physical entities and embodied states.
HADREB: Human Appraisals and (English) Descriptions of Robot Emotional Behaviors
To address this gap we have collected HADREB, a dataset of human appraisals and English descriptions of robot emotional behaviors collected from over 30 participants.
rrSDS: Towards a Robot-ready Spoken Dialogue System
Spoken interaction with a physical robot requires a dialogue system that is modular, multimodal, distributive, incremental and temporally aligned.
Learning Word Groundings from Humans Facilitated by Robot Emotional Displays
In working towards accomplishing a human-level acquisition and understanding of language, a robot must meet two requirements: the ability to learn words from interactions with its physical environment, and the ability to learn language from people in settings for language use, such as spoken dialogue.
Unsupervised, Bottom-up Category Discovery for Symbol Grounding with a Curious Robot
Towards addressing the Symbol Grounding Problem and motivated by early childhood language development, we leverage a robot which has been equipped with an approximate model of curiosity with particular focus on bottom-up building of unsupervised categories grounded in the physical world.
Dialogue with Robots: Proposals for Broadening Participation and Research in the SLIVAR Community
The ability to interact with machines using natural human language is becoming not just commonplace, but expected.
Understanding Survey Paper Taxonomy about Large Language Models via Graph Representation Learning
As new research on Large Language Models (LLMs) continues, it is difficult to keep up with new research and models.
A Multi-Perspective Learning to Rank Approach to Support Children's Information Seeking in the Classroom
We introduce a novel re-ranking model that aims to augment the functionality of standard search engines to support classroom search activities for children (ages 6 to 11).
On the Computational Modeling of Meaning: Embodied Cognition Intertwined with Emotion
This document chronicles this author's attempt to explore how words come to mean what they do, with a particular focus on child language acquisition and what that means for models of language understanding.\footnote{I say \emph{historical} because I synthesize the ideas based on when I discovered them and how those ideas influenced my later thinking.}
Vision Language Transformers: A Survey
Vision language tasks, such as answering questions about or generating captions that describe an image, are difficult tasks for computers to perform.
Who's in Charge? Roles and Responsibilities of Decision-Making Components in Conversational Robots
Software architectures for conversational robots typically consist of multiple modules, each designed for a particular processing task or functionality.
Evaluating Automatic Speech Recognition in an Incremental Setting
The increasing reliability of automatic speech recognition has proliferated its everyday use.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Conversational Agents and Children: Let Children Learn
Using online information discovery as a case study, in this position paper we discuss the need to design, develop, and deploy (conversational) agents that can -- non-intrusively -- guide children in their quest for online resources rather than simply finding resources for them.
The State of SLIVAR: What's next for robots, human-robot interaction, and (spoken) dialogue systems?
We synthesize the reported results and recommendations of recent workshops and seminars that convened to discuss open questions within the important intersection of robotics, human-robot interaction, and spoken dialogue systems research.
An Analysis of the Recent Visibility of the SigDial Conference
Automated speech and text interfaces are continuing to improve, resulting in increased research in the area of dialogue systems.
Language Acquisition is Embodied, Interactive, Emotive: a Research Proposal
Humans' experience of the world is profoundly multimodal from the beginning, so why do existing state-of-the-art language models only use text as a modality to learn and represent semantic meaning?
CASTing a Net: Supporting Teachers with Search Technology
In this paper, we argue for the need to broaden the research focus to include teachers and how search technology can aid them.
Evaluating and Improving Child-Directed Automatic Speech Recognition
Speech recognition has seen dramatic improvements in the last decade, though those improvements have focused primarily on adult speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
KidSpell: A Child-Oriented, Rule-Based, Phonetic Spellchecker
For help with their spelling errors, children often turn to spellcheckers integrated in software applications like word processors and search engines.
Composing and Embedding the Words-as-Classifiers Model of Grounded Semantics
The words-as-classifiers model of grounded lexical semantics learns a semantic fitness score between physical entities and the words that are used to denote those entities.
Incrementalizing RASA's Open-Source Natural Language Understanding Pipeline
As spoken dialogue systems and chatbots are gaining more widespread adoption, commercial and open-sourced services for natural language understanding are emerging.
Predicting Perceived Age: Both Language Ability and Appearance are Important
When interacting with robots in a situated spoken dialogue setting, human dialogue partners tend to assign anthropomorphic and social characteristics to those robots.
Symbol, Conversational, and Societal Grounding with a Toy Robot
Essential to meaningful interaction is grounding at the symbolic, conversational, and societal levels.
PentoRef: A Corpus of Spoken References in Task-oriented Dialogues
PentoRef is a corpus of task-oriented dialogues collected in systematically manipulated settings.
Resolving References to Objects in Photographs using the Words-As-Classifiers Model
A common use of language is to refer to visually present objects.
