Current perceptions of Instant Messaging (IM) use are based primarily on self-report studies. We logged thousands of (mostly) workplace IM conversations and evaluated their conversational characteristics and functions. Contrary to prior research, we found that the primary use of workplace IM was for complex work discussions. Only 28% of conversations were simple, single-purpose interactions and only 31% were about scheduling or coordination. Moreover, people rarely switched from IM to another medium when the conversation got complex. We found evidence of two distinct styles of use. Heavy IM users and frequent IM partners mainly used it to work together: to discuss a broad range of topics via many fastpaced interactions per day, each with many short turns and much threading and multitasking. Light users and infrequent pairs mainly used IM to coordinate: for scheduling, via fewer conversations per day that were shorter, slower-paced with less threading and multitasking.

Current perceptions of Instant Messaging (IM) use are based primarily on self-report studies. We logged thousands of (mostly) workplace IM conversations and evaluated their conversational characteristics and functions. Contrary to prior research, we found that the primary use of workplace IM was for complex work discussions. Only 28% of conversations were simple, single-purpose interactions and only 31% were about scheduling or coordination. Moreover, people rarely switched from IM to another medium when the conversation got complex. We found evidence of two distinct styles of use. Heavy IM users and frequent IM partners mainly used it to work together: to discuss a broad range of topics via many fastpaced interactions per day, each with many short turns and much threading and multitasking. Light users and infrequent pairs mainly used IM to coordinate: for scheduling, via fewer conversations per day that were shorter, slower-paced with less threading and multitasking.

The design of methods for performance evaluation is a major open research issue in the area of spoken language dialogue systems. In this paper we present the PARADISE methodology for developing predictive models of spoken dialogue performance, and then show how to evaluate the predictive power and generalizability of such models. To illustrate our methodology, we develop a number of models for predicting system usability (as measured by user satisfaction), based on the application of PARADISE to experimental data from three di erent spoken dialogue systems. We then measure the extent to which our models generalize across di erent systems, di erent experimental conditions, and di erent user populations, by testing models trained on a subset of our corpus against a test set of dialogues. Our results show that our models generalize well across our three systems, and are thus a rst approximation towards a general performance model of system usability.

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The purpose of this experiment was to determine the applicability of the Articulation Index (AI) model for characterizing the speech recognition performance of listeners with mild-to-moderate hearing loss. Performance-intensity functions were obtained from five normal-hearing listeners and 11 hearing-impaired listeners using a closed-set nonsense syllable test for two frequency responses (uniform and high-frequency emphasis). For each listener, the fitting constant Q of the nonlinear transfer function relating AI and speech recognition was estimated. Results indicated that the function mapping AI onto performance was approximately the same for normal and hearing-impaired listeners with mild-to-moderate hearing loss and high speech recognition scores. For a hearing-impaired listener with poor speech recognition ability, the AI procedure was a poor predictor of performance. The AI procedure as presently used is inadequate for predicting performance of individuals with reduced speech recognition ability and should be used conservatively in applications predicting optimal or acceptable frequency response characteristics for hearing-aid amplification systems.