Situated language understanding for a spoken dialog system within vehicles

Misu, Teruhisa; Raux, Antoine; Gupta, Rakesh K.; Lane, Ian

doi:10.1016/j.csl.2015.02.002

Cited by 10 publications

(4 citation statements)

References 19 publications

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“…The article Situated language understanding for a spoken dialogue system within vehicles of authors Misu et al (2015) studies situated language understanding in a mobile in-car system that can answer questions about the user's surroundings. The authors propose methods for understanding user queries taking into account changes in spatial relationships between the car and target buildings.…”

Section: Language Understandingmentioning

confidence: 99%

Introduction for Speech and language for interactive robots

Cuayáhuitl

Komatani

Skantze

2015

Computer Speech & Language

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This special issue includes research articles which apply spoken language processing to robots that interact with human users through speech, possibly combined with other modalities. Robots that can listen to human speech, understand it, interact according to the conveyed meaning, and respond represent major research and technological challenges. Their common aim is to equip robots with natural interaction abilities. However, robotics and spoken language processing are areas that are typically studied within their respective communities with limited communication across disciplinary boundaries. The articles in this special issue represent examples that address the need for an increased multidisciplinary exchange of ideas. © 2015 Published by Elsevier Ltd.Keywords: Interactive robots; Speech localisation; Dialogue management; Multimodal interaction; Speech synthesis; Human-robot interaction Aim and scopeSpeech-based communication with robots faces important challenges in pushing current technology over the edge of usability in real world scenarios. In contrast to conventional interactive systems, a talking robot always needs to take its physical environment into account when communicating with users. Environments are typically unstructured, dynamic and noisy and therefore challenging for robots. The objective of this special issue is to highlight research that applies speech and language processing to robots that interact with people through speech as the main modality of interaction. For example, a robot may need to communicate with users via distant speech recognition and understand with constantly changing degrees of noise.Alternatively, the robot may coordinate its verbal and non-verbal turn-taking behaviours as when generating speech and gestures at the same time. Speech and language technologies have huge potential to equip robots that interact naturally with their human users. However, the effectiveness of interactive robots needs to be demonstrated in real (or at least realistic) environments. This special issue presents some case studies. Articles in the special issueThis special issue received a total of 20 submissions, 11 of which were originally accepted for publication. Each accepted article went through two or three rounds of reviewing, and each submission was assigned two or three reviewers. The contents of this special issue cover the following four broad topics, which are vital for interactive robots across domains:http://dx

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Section: Language Understandingmentioning

confidence: 99%

Introduction for Speech and language for interactive robots

Cuayáhuitl

Komatani

Skantze

2015

Computer Speech & Language

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“…And multimodal conversation becomes daily activities for mobile phone users. These advances have extended the initial application domains of conversational interfaces to complex information retrieval and question answering applications (Metze et al, 2014), ecommerce systems (Tsai, 2005), surveys applications (Stent et al, 2006), in-car systems (Hofmann et al, 2014), remote control of devices and robots in smart environments (Minker et al, 2010), elearning and tutoring systems (Kopp et al, 2012), communication within vehicles (Misu et al, 2015), Ambient Assisted Living systems (Bickmore et al, 2010), recommendation systems (Reschke et al, 2013), or virtual companions (Horchak et al, 2014). Griol et.el.…”

Section: Introductionmentioning

confidence: 99%

Mobile App for Maize: State of the Art, Potential Areas, and Future Directions in Bangladesh

Hasan¹,

Haque²,

Haque³

et al. 2019

Am. J. Agric. Sci. Eng. Technol.

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The mobile phone is no longer just a communication device, but also an essential part of people’s entertainment and daily life. Now android system in the electronics market is becoming more and more popular, especially in the smartphone market. The most popular smartphone application is games followed by listening to music, watching videos, communicating with social media, exploring photos, taking selfies, etc. Mobile apps also become more popular than desktop computer-based software. The mobile phone is used for different purposes activities from simple communication to video conferencing, from playing games to the utilization of apps for day to day life. Since Mobile networks reach every corner of Bangladesh, it is now a potential time to use the mobile phone for providing need-based information to the farming communities for their benefit. Since Bangladesh is an agriculture-based country and most of the farming communities subsist in the northern part of Bangladesh. It was found that Nilphamari (Northern district of Bangladesh) suitable area for providing benefits to the farming communities by developing a mobile app. The researchers chose the disease identification and their’ management for the Maize crop as Maize is the 3rd most common in that area. This paper mainly discussed two sections; 1. The application interface in the Bengali language with multimodal function; text, voice with the local language, and images; 2. Feedback from the users about the app. It was found that most of the end-users were able to properly identify the diseases and manage them well.

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“…59,78,67,81 Thus, these interfaces make technologies more usable, as they ease interaction with devices such as smartphones and tablets, 69 allow integration in different environments, 34 facilitate the interaction with different systems 86 and make technologies more accessible, especially for disabled people. 107,20 The performance of spoken language dialog systems has improved over time, extending the initial application domains to complex information retrieval and question answering applications, 71 surveys applications, 100 e-commerce systems, 105 recommendations systems, 85 e-learning and tutoring systems, 54 in-car systems, 38 spoken dialog within vehicles, 73 remote control of devices and robots in smart envi-ronments, 72 Ambient Assisted Living systems, 8 or embodied dialog systems and companions. 39 The described systems are usually designed adhoc for their specific domain using rule-based dialog models and standards in which developers must specify the steps to be followed by the system.…”

Section: Introductionmentioning

confidence: 99%

A Two-Stage Combining Classifier Model for the Development of Adaptive Dialog Systems

Griol

Iglesias

Ledezma

et al. 2016

Int. J. Neur. Syst.

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This paper proposes a statistical framework to develop user-adapted spoken dialog systems. The proposed framework integrates two main models. The first model is used to predict the user's intention during the dialog. The second model uses this prediction and the history of dialog up to the current moment to predict the next system response. This prediction is performed with an ensemble-based classifier trained for each of the tasks considered, so that a better selection of the next system can be attained weighting the outputs of these specialized classifiers. The codification of the information and the definition of data structures to store the data supplied by the user throughout the dialog makes the estimation of the models from the training data and practical domains manageable. We describe our proposal and its application and detailed evaluation in a practical spoken dialog system.

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Situated language understanding for a spoken dialog system within vehicles

Cited by 10 publications

References 19 publications

Introduction for Speech and language for interactive robots

Introduction for Speech and language for interactive robots

Mobile App for Maize: State of the Art, Potential Areas, and Future Directions in Bangladesh

A Two-Stage Combining Classifier Model for the Development of Adaptive Dialog Systems

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