WordNet is a lexical database of the English language that seeks to capture the relationships between words as a graph data structure [8]. In the WordNet graph, vertices represent word groupings of synonyms, while edges are labeled relations between either two specific words in a grouping or two synonym groupings. The richness of these relationships allow WordNet to encode information about the...

We present a novel conversational language model that is grounded with information about facial expressions. To our knowledge this is the first in-depth examination of grounding natural language models with facial cues. We train a neural language model that uses automatically detected facial action unit intensity information in images alongside text to generate conversational dialogue. We evalu...

In this paper, we describe a new pervasive conversational system that provides access to multiple desktop applications, from multiple client devices, using multiple input modalities. Client devices currently supported include desktop and telephone, and the applications incorporated include email, calendarand address book. When the access is from a desktop, both conversational natural language a...

This paper describes a conversational agent for language learning. Our goal is to provide an environment that allows learners to practice language skills by interacting with other learners and artificial conversational agents using instant messaging and email. The learners take part in an adventure story and must use dialogues that are typically found in basal language textbooks to move forward...

The conversational agent understands and provides users with proper information based on natural language. Conventional agents based on pattern matching have many restrictions to manage various types of real dialogues and to improve the answering performance. For the effective construction of conversational agents, we propose a domain-adaptive conversational agent that infers the user’s intenti...

This paper reviews the 2009 NIST Language Recognition Evaluation (LRE09), the most recent in a series held since 1996, which have evaluated automatic systems for language recognition. The 2009 evaluation was notable for including a larger number of target and non-target languages, for primarily utilizing “found” narrowband conversational broadcast data from the Voice of America, and for includi...

Children's early language exposure impacts their later linguistic skills, cognitive abilities, and academic achievement, and large disparities in language exposure are associated with family socioeconomic status (SES). However, there is little evidence about the neural mechanisms underlying the relation between language experience and linguistic and cognitive development. Here, language experie...

According to discourse theories in linguistics, conversational utterances possess an informational structure that partitions each sentence into two portions: a “given” and “new”. In this work, we explore this idea by building sub-sentence discourse language models for conversational speech recognition. The internal sentence structure is captured in statistical language modeling by training mult...

We describe CARDIAC, a prototype for an intelligent conversational assistant that provides health monitoring for chronic heart failure patients. CARDIAC supports user initiative through its ability to understand natural language and connect it to intention recognition. The natural language interface allows patients to interact with CARDIAC without special training. The system is designed to und...

Although data-driven techniques are commonly used for Natural Language Understanding in dialogue systems, their efficacy is often hampered by the lack of appropriate annotated training data in sufficient amounts. We present an approach for rapid and cost-effective annotation of training data for classification-based language understanding in conversational dialogue systems. Experiments using a ...