Karen P. Tang

Are GSM Phones THE Solution for Localization

In this paper, we argue that localization solution based on cellular phone technology, specifically GSM phones, is a sufficient and attractive option in terms of coverage and accuracy for a wide range of indoor, outdoor, and placebased location-aware applications. We present preliminary results that indicate that GSM-based localization systems have the potential to detect the places that people visit in their everyday lives, and can achieve median localization accuracies of 5 and 75 meters for indoor and outdoor environments, respectively.

Examining task engagement in sensor-based statistical models of human interruptibility

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.

Generating phonetic cognates to handle named entities in English-Chinese cross-language spoken document retrieval

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 improvement by including the use of named entities in this way.

Putting people in their place: an anonymous and privacy-sensitive approach to collecting sensed data in location-based applications

The emergence of location-based computing promises new and compelling applications, but raises very real privacy risks. Existing approaches to privacy generally treat people as the entity of interest, often using a fidelity tradeoff to manage the costs and benefits of revealing a persons location. However, these approaches cannot be applied in some applications, as a reduction in precision can render location information useless. This is true of a category of applications that use location data collected from multiple people to infer such information as whether there is a traffic jam on a bridge, whether there are seats available in a nearby coffee shop, when the next bus will arrive, or if a particular conference room is currently empty. We present hitchhiking, a new approach that treats locations as the primary entity of interest. Hitchhiking removes the fidelity tradeoff by preserving the anonymity of reports without reducing the precision of location disclosures. We can therefore support the full functionality of an interesting class of location-based applications without introducing the privacy concerns that would otherwise arise.

User-Controllable Security and Privacy for Pervasive Computing

We describe our current work in developing novel mechanisms for managing security and privacy in pervasive computing environments. More specifically, we have developed and evaluated three different applications, including a contextual instant messenger, a people finder application, and a phone-based application for access control. We also draw out some themes we have learned thus far for user-controllable security and privacy.

Field deployment of IMBuddy: a study of privacy control and feedback mechanisms for contextual IM

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 IMBuddys 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 rule-based privacy control intuitive and easy to use. Furthermore, the set of feedback mechanisms provided users with a good awareness of what was disclosed.

Mandarin-English Information (MEI): investigating translingual speech retrieval

This paper describes the Mandarin-English Information (MEI) project, where we investigated the problem of cross-language spoken document retrieval (CL-SDR), and developed one of the first English-Chinese CL-SDR systems. Our system accepts an entire English news story (text) as query, and retrieves relevant Chinese broadcast news stories (audio) from the document collection. Hence this is a cross-language and cross-media retrieval task. We applied a multi-scale approach to our problem, which unifies the use of phrases, words and subwords in retrieval. The English queries are translated into Chinese by means of a dictionary-based approach, where we have integrated phrase-based translation with word-by-word translation. Untranslatable named entities are transliterated by a novel subword translation technique. The multi-scale approach can be divided into three subtasks -- multi-scale query formulation, multi-scale audio indexing (by speech recognition) and multi-scale retrieval. Experimental results demonstrate that the use of phrase-based translation and subword translation gave performance gains, and multi-scale retrieval outperforms word-based retrieval.

Mandarin-English Information (MEI): Investigating translingual speech retrieval

Abstract This paper describes the Mandarin–English Information (MEI) project, where we investigated the problem of cross-language spoken document retrieval (CL-SDR), and developed one of the first English–Chinese CL-SDR systems. Our system accepts an entire English news story (text) as query, and retrieves relevant Chinese broadcast news stories (audio) from the document collection. Hence, this is a cross-language and cross-media retrieval task. We applied a multi-scale approach to our problem, which unifies the use of phrases, words and subwords in retrieval. The English queries are translated into Chinese by means of a dictionary-based approach, where we have integrated phrase-based translation with word-by-word translation. Untranslatable named entities are transliterated by a novel subword translation technique. The multi-scale approach can be divided into three subtasks – multi-scale query formulation, multi-scale audio indexing (by speech recognition) and multi-scale retrieval. Experimental results demonstrate that the use of phrase-based translation and subword translation gave performance gains, and multi-scale retrieval outperforms word-based retrieval.

eWatch: context sensitive system design case study

In this paper, we introduce a novel context sensitive system design paradigm. Multiple sensors/computational architecture, in the form of our eWatch device, is used to infer the activities that the system is encountering, and can provide a platform for context-aware computing. We created an eWatch prototype that senses user activities and notifies them when important messages have arrived. An accelerometer and microphone provide inputs to a model of interruptibility. A vibration motor for tactile feedback and two ultra bright LEDs for visual feedback provide user notification through different vibration patterns and colors. eWatch is transparently integrated into the users environment, and communicates via Bluetooth. This new class of integrated systems underscores the need for new forms of regularity, constraints, and design structure. Our results indicate the power of our method to accurately determine a meaningful context model while only requiring data from our eWatch device.

A context-specific electronic design and prototyping course [sensing and notification wearable computing platform]

This paper describes a context-specific electronic design and prototyping approach in an innovative project course at Carnegie Mellon. We built a sensing and notification wearable computing platform, called eWatch, for context-aware computing. eWatch senses user activities and provides them with urgent notifications. An accelerometer and microphone provide inputs to a model of user interruptibility levels. A vibration motor for tactile feedback and two ultra bright LEDs for visual feedback provide user notification through different vibration patterns and colors. User studies identified appropriate notification schemes for mobile and office settings. Bluetooth communication connects the eWatch to a PDA or desktop computer for sensor data analysis and notification.