Software guides museum-goers

By Kimberly Patch, Technology Research News

Reading the written material that goes along with museum exhibits is always a little tricky. If you're the type who has to read every word, you're likely to see the same background information over and over again, and if you're the type who likes to dip in and out of the text, you'll probably end up missing at least some of background material.

Researchers from Europe have built a system designed to tap the powers of hypertext, information databases, and natural language generation to allow people to go as deeply or as quickly as they wish through the written material in museum-type settings without repeating or missing much. "It occurred to me that... these problems can be addressed by using natural language generation technology," said Jon Oberlander, a reader in cognitive science at the University of Edinburgh.

The information can be displayed in several forms in physical places like museums and virtual spaces like the World Wide Web. "The same information server and generator can dynamically supply information to wireless handhelds in a real museum gallery, or drive synthetic speech over a mobile phone, or build Web pages on-the-fly to describe a virtual gallery," said Oberlander. The system is also designed to work with any language.

There are several inherent problems with museum labels, according to Oberlander. First, they are generally designed to be accessed in any order. This means they must each represent all the relevant information about their object, which can mean overly wordy and redundant descriptions. "Small differences between two objects may be submerged in a sea of similar details," he said. Using traditional labels, the only way to avoid massive redundancies is to force visitors to read the descriptions in a certain order "and that's not great for their sense of freedom," he said.

"Secondly, there's no guarantee that [visitors] will actually find what they need," he added. In contrast, a live curator can find out what museum-goers want, present options, and, if necessary, steer them to objects they were not aware of, said Oberlander.

The researchers' system addresses those problems by generating answers to visitors' questions on-the-fly. It keeps track of what a visitor has seen in order to tailor the descriptions appropriately.

Someone visiting via the Web would start from a page of icons showing a gallery of objects, and when the visitor clicked on a particular icon, a new page would be generated, with a larger image, a title, a description and a list of links to related objects. "At this point they can return to the main page and choose another object, where they can follow one of the suggested links, or they can ask for more information about the current object. Either way a new page is generated for the chosen object [and] the description of the page will take into account what other descriptions have been generated so far, tailoring both content and form," he said.

Under the hood is software that includes four key components: a content potential module, a text planner, a surface realizer and a module that chooses the best presentation for the generated description.

The content potential module keeps track of, and links together, facts extracted from museum databases and curator interviews. It also places different values on each fact, depending on how important the curator judges it to be and how interesting and familiar it is expected to be to the visitor. This familiarity value changes throughout the course of a visit.

When a visitor requests information, the text planner module selects a subset of facts from the content potential module. "It starts from the... selected object, and includes all the facts which are nearby and sufficiently interesting, important and unfamiliar," said Oberlander.

The module takes into consideration the number of facts available for the current type of user, and organizes the information into a coherent order that signals explicitly how the facts fit together, Oberlander said. "The text structure built up this way is still essentially independent of the language which is used to express the information," he said.

The surface realizer takes this abstract information and chooses the best way of expressing it using grammatical constructions, words and connectives. "This is also where the system takes into account the different ways we refer to objects when we mention them the first time, [than] on subsequent occasions," said Oberlander. For example, the first time you mention a designer, you might say 'a British designer named Jessie M. King', then later refer to her as 'Jessie M. King', 'King', or 'she'.

The final module decides whether to wrap the textual description in HTML with live links, send it as pure text, or put it through a speech synthesizer.

In theory, the software can work with any language. The researchers are currently working with English, Italian and Greek. "One of the key challenges in the current project has been to cleanly separate the parts of the system that are independent of English, Italian or Greek from the parts that have to rely on knowledge of the particular language," he said.

In some ways, English is the easy language, Oberlander added. "The sophistication of the system [had] to be considerably increased for languages with complex word-information rules like Greek. But once you've done Greek, Italian is relatively easy," he said. In the end, it shouldn't cost much to add a new language, he said.

As part of the project, the researchers and a partner, the Foundation of the Hellenic World in Athens, have constructed an immersive view of the ancient city of Miletus using the software.

The researchers are also looking to use the software to mine many types of existing textual information, including online catalogs. "It will work with almost any kind of online catalog and in customer relationship management," said Oberlander. The researchers are also planning on using the system for tutoring, he said.

The software combines work in several different areas in a very interesting way, said Paul Aoki, a research scientist at the Xerox Palo Alto Research Center. "They're able to [make] previous technologies really deployable," he said. "You can imagine that typical audio guide content like overviews, jokes and dramatic stories would be tough to generate on-the-fly, but something like [this] could be used to weave pre-recorded pieces together with dynamic factual content."

The overall approach of generating text from a database of descriptive elements could have many uses, Aoki said. "There are many different... scenarios where this kind of technology can be applied -- walks through historic districts, botanic gardens, historic houses. Another example might be an audio restaurant guide that knows you care about parking and price... and gives you natural-sounding descriptions that are tailored to those preferences," he said.

Oberlander's research colleagues were Ion Androutsopoulos and Aggeliki Dimitromanolaki of the Greek National Center for Scientific Research in Greece, Vassiliki Kokkinhai of the Foundation of the Hellenic World in Greece, Jo Calder of the University of Edinburgh, and Elena Not of the Trentino Cultural Institute in Italy. They presented the research at the 29th Conference on Computer Applications and Quantitative Methods in Archeology held in Gotland, Sweden, April 25 to 29, 2001. The research was funded by the European Union.

Timeline:   Now
Funding:   Government
TRN Categories:  Human-Computer Interaction; Databases and Information Retrieval
Story Type:   News
Related Elements:  Technical paper, "Generating Multilingual Personalize Descriptions of Museum Exhibits -- The M-PIRO Project," presented 29th Conference on Computer Applications and Quantitative Methods in Archeology in Gotland, Sweden, April 25-29, 2001.


June 12/19, 2002

Page One

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