Bernard S. Renger

Geotracker: geospatial and temporal RSS navigation

The Web is rapidly moving towards a platform for mass collaboration in content production and consumption. Fresh content on a variety of topics, people, and places is being created and made available on the Web at breathtaking speed. Navigating the content effectively not only requires techniques such as aggregating various RSS-enabled feeds, but it also demands a new browsing paradigm. In this paper, we present novel geospatial and temporal browsing techniques that provide users with the capability of aggregating and navigating RSS-enabled content in a timely, personalized and automatic manner. In particular, we describe a system called GeoTracker that utilizes both a geospatial representation and a temporal (chronological) presentation to help users spot the most relevant updates quickly. Within the context of this work, we provide a middleware engine that supports intelligent aggregation and dissemination of RSS feeds with personalization to desktops and mobile devices. We study the navigation capabilities of this system on two kinds of data sets, namely, 2006 World Cup soccer data collected over two months and breaking news items that occur every day. We also demonstrate that the application of such technologies to the video search results returned by YouTube and Google greatly enhances a user.s ability in locating and browsing videos based on his or her geographical interests. Finally, we demonstrate that the location inference performance of GeoTracker compares well against machine learning techniques used in the natural language processing/information retrieval community. Despite its algorithm simplicity, it preserves high recall percentages.

GeoTV: navigating geocoded rss to create an iptv experience

The Web is rapidly moving towards a platform for mass collaboration in content production and consumption from three screens: computers, mobile phones, and TVs. While there has been a surge of interests in making Web content accessible from mobile devices, there is a significant lack of progress when it comes to making the web experience suitable for viewing on a television. Towards this end, we describe a novel concept, namely GeoTV, where we explore a framework by which web content can be presented or pushed in a meaningful manner to create an entertainment experience for the TV audience. Fresh content on a variety of topics, people, and places is being created and made available on the Web at breathtaking speed. Navigating fresh content effectively on TV demands a new browsing paradigm that requires fewer mouse clicks or user interactions from the remote control. Novel geospatial and temporal browsing techniques are provided in GeoTV that allow users the capability of aggregating and navigating RSS-enabled content in a timely, personalized and automatic manner for viewing in an IPTV environment. This poster is an extension of our previous work on GeoTracker that utilizes both a geospatial representation and a temporal (chronological) presentation to help users spot the most relevant updates quickly within the context of a Web-enabled environment. We demonstrate 1) the usability of such a tool that greatly enhances a user.s ability in locating and browsing videos based on his or her geographical interests and 2) various innovative interface designs for showing RSS-enabled information in an IPTV environment.

MediaAlert - a broadcast video monitoring and alerting system for mobile users

We present a system for automatic monitoring and timely dissemination of multimedia information to a range or mobile information appliances based on each users interest profile. Multimedia processing algorithms detect and isolate relevant video segments from over twenty television broadcast programs based on a collection or words and phrases specified by the user. Content repurposing techniques are then used to convert the information into a form that is suitable for delivery to the users mobile devices. Alerts are sent using a number of application messaging and network access protocols including email, short message service (SMS), multimedia messaging service (MMS), voice, session initiation protocol (SIP), fax, and pager protocols. The system is evaluated with respect to performance and user experiences. The MediaAlert system provides an effective and low-cost solution for the timely generation of alerts containing personal, business, and security information.

Bootstrapping spoken dialogue systems by exploiting reusable libraries

Building natural language spoken dialogue systems requires large amounts of human transcribed and labeled speech utterances to reach useful operational service performances. Furthermore, the design of such complex systems consists of several manual steps. The User Experience (UE) expert analyzes and defines by hand the system core functionalities: the system semantic scope (call-types) and the dialogue manager strategy that will drive the human–machine interaction. This approach is extensive and error-prone since it involves several nontrivial design decisions that can be evaluated only after the actual system deployment. Moreover, scalability is compromised by time, costs, and the high level of UE know-how needed to reach a consistent design. We propose a novel approach for bootstrapping spoken dialogue systems based on the reuse of existing transcribed and labeled data, common reusable dialogue templates, generic language and understanding models, and a consistent design process. We demonstrate that our approach reduces design and development time while providing an effective system without any application-specific data.

A system for searching and browsing spoken communications

As the amount of spoken communications accessible by computers increases, searching and browsing is becoming crucial for utilizing such material for gathering information. It is desirable for multimedia content analysis systems to handle various formats of data and to serve varying user needs while presenting a simple and consistent user interface. In this paper, we present a research system for searching and browsing spoken communications. The system uses core technologies such as speaker segmentation, automatic speech recognition, transcription alignment, keyword extraction and speech indexing and retrieval to make spoken communications easy to navigate. The main focus is on telephone conversations and teleconferences with comparisons to broadcast news.

VoiSTV: voice-enabled social TV

Until recently, the TV viewing experience has not been a very social activity compared to activities on the World Wide Web. In this work, we will present a Voice-enabled Social TV system (VoiSTV) which allows users to interact, follow and monitor the online social media messages related to a TV show while watching it. Users can create, send, and reply to messages using spoken language. VoiSTV also provides metadata information about TV shows such as trends, hot topics, popularity as well as aggregated sentiment of show-related messages, all of which are valuable for TV program search and recommendation.

Project GeoTV - A Three-Screen Service: Navigate on SmartPhone, Browse on PC, Watch on HDTV

GeoTV is a project that explores seamless integration of mobile phones, HDTV sets, and computers in the living room to enrich the user experience of existing services. The three- screen service allows a user to navigate a world map on a smart phone to track geo-located media RSS content that matches her personal interests. The user can show a matching video clip on her phone or direct a nearby HDTV set to play the video. In addition, the user can bring up a world map on a nearby computer screen to navigate areas of interest related to the video clip. GeoTV allows all three screens to be used for what they are best for: HDTV for high resolution video, computer screen for browsing a world map, and a smart phone for personalized control at hand to select media of interest.

Semantic data mining of short utterances

This paper introduces a methodology for speech data mining along with the tools that the methodology requires. We show how they increase the productivity of the analyst who seeks relationships among the contents of multiple utterances and ultimately must link some newly discovered context into testable hypotheses about new information. While, in its simplest form, one can extend text data mining to speech data mining by using text tools on the output of a speech recognizer, we have found that it is not optimal. We show how data mining techniques that are typically applied to text should be modified to enable an analyst to do effective semantic data mining on a large collection of short speech utterances. For the purposes of this paper, we examine semantic data mining in the context of semantic parsing and analysis in a specific situation involving the solution of a business problem that is known to the analyst. We are not attempting a generic semantic analysis of a set of speech. Our tools and methods allow the analyst to mine the speech data to discover the semantics that best cover the desired solution. The coverage, in this case, yields a set of Natural Language Understanding (NLU) classifiers that serve as testable hypotheses.

A Novel Architecture for Content and Delivery Validation for IPTV Systems

In this paper, we describe a novel architecture for content and delivery validation for IPTV systems. The system generates multimedia events derived from IPTV content analysis and its delivery. Events are aggregated, filtered and, through a rules-based system, processed and prioritized to provide monitoring and alerting capabilities. Offline event processing along with a video archiving capability allows for detailed forensic analysis. The novelty of the approach includes the correlation and the combination of content-specific and network-specific events in a normalized representation to allow for complex forensic monitoring and alerting. Applications include content security assurance and metadata verification.