Interpreting Symptoms of Cognitive Load in Speech Input

Berthold, André; Jameson, Anthony

doi:10.1007/978-3-7091-2490-1_23

Cited by 66 publications

(65 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In , physical appearance features extracted from realtime videos are used to assess users' fatigue status. The work by (Berthold and Jameson, 1999) studies the effects of cognitive workload on two speech symptoms -sentence fragments and articulation rate. Cowie and co-workers (Cowie et al, 2001) develop a hybrid system capable of using information from faces and voices to recognize people's emotions.…”

Section: General Approachesmentioning

confidence: 99%

Toward a decision-theoretic framework for affect recognition and user assistance

Liao

Zhang

Zhu

et al. 2006

International Journal of Human-Computer Studies

View full text Add to dashboard Cite

There is an increasing interest in developing intelligent human-computer interaction systems that can fulfill two functions -recognizing user affective states and providing the user with timely and appropriate assistance. In this paper, we present a general unified decision-theoretic framework based on Influence Diagrams for simultaneously modeling user affect recognition and assistance. Affective state recognition is achieved through active probabilistic inference from the available multi-modality sensory data. User assistance is automatically accomplished through a decisionmaking process that balances the benefits of keeping the user in productive affective states and the costs of performing user assistance. We discuss three theoretical issues within the framework, namely, user affect recognition, active sensory action selection, and user assistance. Validation of the proposed framework via a simulation study demonstrates its capability in efficient user affect recognition as well as timely and appropriate user assistance. Besides the theoretical contributions, we build a non-invasive real-time prototype system to recognize different user affective states (stress and fatigue) from four-modality user measurements, namely physical appearance features, physiological measures, user performance, and behavioral data. The affect recognition component of the prototype system is subsequently validated through a real world study involving human subjects.

show abstract

Section: General Approachesmentioning

confidence: 99%

Toward a decision-theoretic framework for affect recognition and user assistance

Liao

Zhang

Zhu

et al. 2006

International Journal of Human-Computer Studies

View full text Add to dashboard Cite

show abstract

“…2 Perhaps more surprisingly, they increased to almost the same extent when the speaker was not under time pressure (…”

Section: Resultsmentioning

confidence: 92%

Recognizing Time Pressure and Cognitive Load on the Basis of Speech: An Experimental Study

et al. 2001

Self Cite

View full text Add to dashboard Cite

Abstract.In an experimental environment, we simulated the situation of a user who gives speech input to a system while walking through an airport. The time pressure on the subjects and the requirement to navigate while speaking were manipulated orthogonally. Each of the 32 subjects generated 80 utterances, which were coded semi-automatically with respect to a wide range of features, such as filled pauses. The experiment yielded new results concerning the effects of time pressure and cognitive load on speech. To see whether a system can automatically identify these conditions on the basis of speech input, we had this task performed for each subject by a Bayesian network that had been learned on the basis of the experimental data for the other subjects. The results shed light on the conditions that determine the accuracy of such recognition.

show abstract

“…In particular, they described a Bayesian representation, inference strategies and control procedures that can be used to infer speaker goals from linguistic and other inputs, to control question asking, and to control dialogue £ow. As discussed below, Berthold and Jameson (1999) used a BN to assess the cognitive load of a user, and Chu-Carroll and Brown (1998) used Dempster^Shafer theory for modeling mixed initiative.…”

Section: Natural Language and User Modelingmentioning

confidence: 99%

Untitled

Zukerman

Litman

2001

User Modeling and User-Adapted Interaction

View full text Add to dashboard Cite

Abstract. The ¢elds of user modeling and natural language processing have been closely linked since the early days of user modeling. Natural language systems consult user models in order to improve their understanding of users' requirements and to generate appropriate and relevant responses. At the same time, the information natural language systems obtain from their users is expected to increase the accuracy of their user models. In this paper, we review natural language systems for generation, understanding and dialogue, focusing on the requirements and limitations these systems and user models place on each other.We then propose avenues for future research.

show abstract

Interpreting Symptoms of Cognitive Load in Speech Input

Cited by 66 publications

References 4 publications

Toward a decision-theoretic framework for affect recognition and user assistance

Toward a decision-theoretic framework for affect recognition and user assistance

Recognizing Time Pressure and Cognitive Load on the Basis of Speech: An Experimental Study

Untitled

Contact Info

Product

Resources

About