The computer and communication systems that office workers currently use tend to interrupt at inappropriate times or unduly demand attention because they have no way to determine when an interruption is appropriate. Sensor-based statistical models of human interruptibility offer a potential solution to this problem. Prior work to examine such models has primarily reported results related to social engagement, but it seems that task engagement is also important. Using an approach developed in our prior work on sensor-based statistical models of human interruptibility, we examine task engagement by studying programmers working on a realistic programming task. After examining many potential sensors, we implement a system to log low-level input events in a development environment. We then automatically extract features from these low-level event logs and build a statistical model of interruptibility. By correctly identifying situations in which programmers are non-interruptible and minimizing cases where the model incorrectly estimates that a programmer is non-interruptible, we can support a reduction in costly interruptions while still allowing systems to convey notifications in a timely manner.
We have developed a technique for automatic transliteration of named entities for English-Chinese cross-language spoken document retrieval (CL-SDR). Our retrieval system integrates machine translation, speech recognition and information retrieval technologies. An English news story forms a textual query that is automatically translated into Chinese words, which are mapped into Mandarin syllables by pronunciation dictionary lookup. Mandarin radio news broadcasts form spoken documents that are indexed by word and syllable recognition. The information retrieval engine performs matching in both word and syllable scales. The English queries contain many named entities that tend to be out-of-vocabulary words for machine translation and speech recognition, and are omitted in retrieval. Names are often transliterated across languages and are generally important for retrieval. We present a technique that takes in a name spelling and automatically generates a phonetic cognate in terms of Chinese syllables to be used in retrieval. Experiments show consistent retrieval performance improvements by including the use of named entities in this way.
We describe a system which supports English text queries searching for Mandarin Chinese spoken documents. This is one of the first attempts to tightly couple speech recognition with machine translation technologies for cross-media and cross-language retrieval. The Mandarin Chinese news audio are indexed with word and subword units by speech recognition. Translation of these multiscale units can effect cross-language information retrieval.The integrated technologies will be evaluated based on the performance of translingnal speech retrieval.
Previous research has shown that design features that support privacy are essential for new technologies looking to gain widespread adoption. As such, privacy-sensitive design will be important for the adoption of social robots, as they could introduce new types of privacy risks to users. In this paper, we report findings from our preliminary study on users' perceptions and attitudes toward privacy in human-robot interaction, based on interviews that we conducted about a workplace social robot.
Abstract. We describe the design of privacy controls and feedback mechanisms for contextual IM, an instant messaging service for disclosing contextual information. We tested our designs on IMBuddy, a contextual IM service we developed that discloses contextual information, including interruptibility, location, and the current window in focus (a proxy for the current task). We deployed our initial design of IMBuddy's privacy mechanisms for two weeks with ten IM users. We then evaluated a redesigned version for four weeks with fifteen users. Our evaluation indicated that users found our group-level rulebased privacy control intuitive and easy to use. Furthermore, the set of feedback mechanisms provided users with a good awareness of what was disclosed.
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