JUPlTER: a telephone-based conversational interface for weather information

Zue, Victor W.; Seneff, Stephanie; Glass, James; Polifroni, Joseph; Pao, Christine; Hazen, Timothy J.; Hetherington, Lee

doi:10.1109/89.817460

Cited by 307 publications

(139 citation statements)

References 14 publications

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“…Similarly, some of the domains that have been exploited by spoken dialogue system designers are well suited for the interface metaphor, since speech is indeed an alternative interface in these domains: (a) information retrieval systems, such as train time table information or directory inquiries (e.g. Aust et al, 1995;Blomberg et al, 1993;Peckham, 1991;Seneff et al, 1998;Zue et al, 2000); (b) ordering and transactions , such as ticket booking (e.g. Boye et al, 1999;Wahlster et al, 2001); (c) command control systems, such as smart homes ("turn the radio off") or voice command shortcuts ("save") (e.g.…”

Section: Opting For Human-likenessmentioning

confidence: 99%

Towards human-like spoken dialogue systems

Edlund¹,

Gustafson²,

Heldner³

et al. 2008

Speech Communication

105

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Section: Opting For Human-likenessmentioning

confidence: 99%

Towards human-like spoken dialogue systems

Edlund¹,

Gustafson²,

Heldner³

et al. 2008

Speech Communication

105

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show abstract

“…Spoken dialogue systems are presently available both in laboratories and commercially for many purposes, such as train timetable inquiry [5], weather inquiry [33], flight reservations [25], and bus schedule guidance [23]. There are also some groups who have developed interesting multimodal applications on mobile platforms or backed by a geographical database, such as "AdApt" [8], "MATCH" [12], "SmartWeb" [29], and "CHAT" [30].…”

Section: Problem Formulationmentioning

confidence: 99%

Harvesting and Summarizing User-Generated Content for Advanced Speech-Based HCI

Liu¹,

Seneff²,

Zue³

2012

IEEE J. Sel. Top. Signal Process.

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Abstract-There are many Web-based platforms where people could share user-generated content such as reviews, posts, blogs, and tweets. However, online communities and social networks are expanding so rapidly that it is impossible for people to digest all the information. To help users obtain information more efficiently, both the interface for data access and the information representation need to be improved. An intuitive and personalized interface, such as a dialogue system, could be an ideal assistant, which engages a user in a continuous dialogue to garner the user's interest, assists the user via speech-navigated interactions, harvests and summarizes the Web data as well as presenting it in a natural way. This work, therefore, aims to conduct research on a universal framework for developing a speech-based interface that can aggregate user-generated content and present the summarized information via speech-based human-computer interactions. The challenge is two-fold. Firstly, how to interpret the semantics and sentiment of user-generated data and aggregate them into structured yet concise summaries? Secondly, how to develop a dialogue modeling mechanism to present the highlighted information via natural language? This work explores plausible approaches to tackling these challenges. We will investigate a parse-and-paraphrase paradigm and a sentiment scoring mechanism for information extraction from unstructured user-generated content. We will also explore sentiment-involved opinion summarization and dialogue modeling approaches for aggregated information representation. A restaurant-domain prototype system has been implemented for demonstration.Index Terms-Spoken dialogue systems, user-generated content processing.

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“…One of the most wide-spread is information retrieval. Some sample applications are tourist and travel information [8,14], weather forecast over the phone [23], speech controlled telephone banking systems [12,13], conference help [5,10], etc. They have also been used for education and training, particularly in improving phonetic and linguistic skills: assistance and guidance to F18 aircraft personnel during maintenance tasks [4], dialog applications for computer-aided speech therapy with different language pathologies [2].…”

Section: Case Study Ii: Railway Station Scenariomentioning

confidence: 99%

Multi-agent System (MAS) Applications in Ambient Intelligence (AmI) Environments

Sánchez-Pi

Mangina

Carbó

et al. 2010

Advances in Intelligent and Soft Computing

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Abstract. Research in context-aware systems has been moving towards reusable and adaptable architectures for managing more advanced human-computer interfaces. Ambient. Intelligence (AmI) investigates computer-based services, which are ubiquitous and based on a variety of objects and devices. Their intelligent and intuitive interfaces act as mediators through which people can interact with the ambient environment. In this paper we present an agent-based architecture which supports the execution of agents in AmI environments. Two case studies are also presented, an airport information system and a railway information system, which uses spoken conversational agents to respond to the user's requests using the contextual information that includes the location information of the user.

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JUPlTER: a telephone-based conversational interface for weather information

Cited by 307 publications

References 14 publications

Towards human-like spoken dialogue systems

Towards human-like spoken dialogue systems

Harvesting and Summarizing User-Generated Content for Advanced Speech-Based HCI

Multi-agent System (MAS) Applications in Ambient Intelligence (AmI) Environments

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