[This post describes research by Fahad Ali and is based on his Msc. thesis]
Contextual constraints (lack of infrastructure, low-literacy etc.) play an important role in ICT for Development (ICT4D) projects. The Kasadaka project offers a technological platform for knowledge sharing applications in rural areas in Sub-Saharan Africa. However, lack of stable internet connections restrict exchange of data between distributed Kasadaka instances, which leads us to research alternative ways of machine-to-machine (m2m) communication.
Fahad Ali’s research focuses on mobile elements and using wifi sneakernets for this m2m to enable information sharing between geographically distributed devices. He developed a Raspberry Pi-based device called the Wifi-donkey that can be mounted on a vehicle and facilitates information exchange with nearby devices, using the built-in wifi card of the rPi 3.The solution is based on Piratebox offline file-sharing and communications system built with free software and uses off-the-shelf Linux software components and configuration settings to allow it to discover and connect to nearby Kasadaka devices based using Wifi technologies.
We evaluated the solution by simulating a low resource setting and testing it by performing so-called “pass-bys” in an Amsterdam residential area. In these cases, SPARQL queries are exchanged between host and client devices and we measure amount of RDF triples transferred. This setup matches earlier case requirements as described in Onno Valkering’s work.Results show that the system works fairly reliably in the simulated setting. The machine-to-machine communication method can be used in various ICT4D projects that require some sort of data sharing functionality.
You can find out more about Fahad’s work through the following resources:
This post describes the MSc theses of Ana-Liza Tjon-a-Pauw and Josien Jansen.
As a semantic web researcher, it is hard to sometimes not see ontologies and triples in aspects of my private life. In this case, through my contacts with dancers and choreographers, I have since a long time been interested in exploring knowledge representation for dance. After a few failed attempts to get a research project funded, I decided to let enthusiastic MSc. students have a go to continue with this exploration. This year, two Information Sciences students, Josien Jansen and Ana-Liza Tjon-a-Pauw, were willing to take up this challenge, with great success. With their background as dancers they did not only have the necessary background knowledge at but also access to dancers who could act as study and test subjects.
The questions of the two projects was therefore: 1) How can we model and represent dance in a sensible manner so that computers can make sense of choreographs and 2) How can we communicate those choreographies to the dancers?
Josien’s thesis addressed this first question. Investigating to what extent choreographers can be supported by semi-automatic analysis of choreographies through the generation of new creative choreography elements. She conducted an online questionnaire among 54 choreographers. The results show that a significant subgroup is willing to use an automatic choreography assistant in their creative process. She further identified requirements for such an assistant, including the semantic levels at which should operate and communicate with the end-users. The requirements are used for a design of a choreography assistant “Dancepiration”, which we implemented as a mobile application. The tool allows choreographers to enter (parts of) a choreography and uses multiple strategies for generating creative variations in three dance styles. Josien evaluated the tool in a user study where we test a) random variations and b) variations based on semantic distance in a dance ontology. The results show that this latter variant is better received by participants. We furthermore identify many differences between the varying dance styles to what extent the assistant supports creativity.
In her thesis, Ana-Liza dove deeper into the human-computer interaction side of the story. Where Josien had classical ballet and modern dance as background and focus, Ana-Liza looked at Dancehall and Hip-Hop dance styles. For her project, Ana-Liza developed four prototypes that could communicate pieces of computer-generated choreography to dancers through Textual Descriptions, 2-D Animations, 3-D Animations, and Audio Descriptions. Each of these presentation methods has its own advantages and disadvantages, so Ana-Liza made an extensive user survey with seven domain experts (dancers). Despite the relatively small group of users, there was a clear preference for the 3-D animations. Based on the results, Ana-Liza also designed an interactive choreography assistant (IDCAT).
The combined theses formed the basis of a scientific article on dance representation and communication that was accepted for publication in the renowned ACE entertainment conference, co-authored by us and co-supervisor Frank Nack.
VU’s Network Institute has a yearly Academy Assistant programme where small interdisciplinary research projects are funded. Within these projects, Master students from different disciplines are given the opportunity to work on these projects under supervision of VU staff members. As in previous years, this year, I also participate as a supervisor in one of these projects, in collaboration with Petra Bos from the Applied Linguistics department. And after having found two enthusiastic students: Dana Hakman from Information Science and Cerise Muller from Applied Linguistics, the project has just started.
Our project “ABC-Kb: A Knowledge base supporting the Assessment of language impairment in Bilingual Children” is aimed at supporting language therapists by (re-)structuring information about language development for bilingual children. Speech language therapists and clinical linguists face the challenge of diagnosing children as young as possible, also when their home language is not Dutch. Their achievements on standard (Dutch) language tests will not be reliable indicators for a language impairment. If diagnosticians had access to information on the language development in the Home Language of these children, this would be tremendously helpful in the diagnostic process.
This project aims to develop a knowledge base (KB) collecting relevant information on the specificities of 60 different home languages (normal and atypical language development), and on contrastive analyses of any of these languages with Dutch. To this end, we leverage an existing wiki: meertaligheidentaalstoornissenvu.wikispaces.com
For her M.Sc. Project, conducted at the Netherlands Institute for Sound and Vision (NISV), Information Sciences student Anggarda Prameswari (pictured right) investigated a local crowdsourcing application to allow NISV to gather crowd annotations for archival audio content. Crowdsourcing and other human computation techniques have proven their use for collecting large numbers of annotations, including in the domain of cultural heritage. Most of the time, crowdsourcing campaigns are done through online tools. Local crowdsourcing is a variant where annotation activities are based on specific locations related to the task.
Anggarda, in collaboration with NISV’s Themistoklis Karavellas, developed a platform called “Elevator Annotator”, to be used on-site. The platform is designed as a standalone Raspberry Pi-powered box which can be placed in an on-site elevator for example. It features a speech recognition software and a button-based UI to communicate with participants (see video below).
The effectiveness of the platform was evaluated in two different locations (at NISV and at Vrije Universiteit) and with two different modes of interaction (voice input and button-based input) through a local crowdsourcing experiment. In this experiments, elevator-travellers were asked to participate in an experiment. Agreeing participants were then played a short sound clip from the collection to be annotated and asked to identify a musical instrument.
The results show that this approach is able to achieve annotations with reasonable accuracy, with up to 4 annotations per hour. Given that these results were acquired from one elevator, this new form of crowdsourcing can be a promising method of eliciting annotations from on-site participants.
Furthermore, a significant difference was found between participants from the two locations. This indicates that indeed, it makes sense to think about localized versions of on-site crowdsourcing.
The Netherlands Institute for Sound and Vision (NISV) archives Dutch broadcast TV and makes it available to researchers, professionals and the general public. One subset are the Polygoonjournaals (Public News broadcasts) that are published under open licenses as part of the OpenImages platform. NISV is also interested in exploring new ways and technologies to make interaction with the material easier and to increase exposure to their archives. In this context, Rudy explored two options.
One part of the research was the autonomous colorization of old black-and-white video footage using Neural Networks. Rudy used a pre-trained NN (Zhang et al 2016) that is able to colorize black and white images. Rudy developed a program to split videos into frames, colorize the individual frames using the NN and then ‘stitch’ them back together into colorized videos. The stunning results were very well received by NISV employees. Examples are shown below.
In the other part of his research, Rudy investigated to what extent the existing news broadcast corpus, with a voice-overs from the famous Philip Bloemendal can be used to develop a modern text-to-speech engine with his voice. To do so he have mainly focused on natural language processing and the determination to what extent the language used by Bloemendal in the 1970s is still comparable enough to contemporary Dutch.
Rudy used precompiled automatic speech recognition (ASR) results to match words to sounds and developed a slot-and-filler text-to-speech system based on this. To increase the limited vocabulary, he implemented a number of strategies, including term-expansion through the use of Open Dutch Wordnet and smart decompounding (this mostly works for Dutch, mapping ‘sinterklaasoptocht’ to ‘sinterklaas’ and ‘optocht’. The different strategies were compared to a baseline. Rudy found that a combination of the two resulted in the best performance (see figure). For more information:
In today’s network society there is a growing need to share, integrate and search in collections of various libraries, archives and museums. For researchers interpreting these interconnected media collections, tools need to be developed. In the exploratory phaseof research the media researcher has no clear focus and is uncertain what to look for in an integrated collection. Data Visualization technology can be used to support strategies and tactics of interest in doing exploratory research
The DIVE tool is an event-based linked media browser that allows researchers to explore interconnected events, media objects, people, places and concepts (see screenshot). Maartje Kruijt’s research project involved investigating to what extent and in what way the construction of narratives can be made possible in DIVE, in such a way that it contributes to the interpretation process of researchers. Such narratives can be either automatically generated on the basis of existing event-event relationships, or be constructed manually by researchers.
The research proposes an extension of the DIVE tool where selections made during the exploratory phase can be presented in narrative form. This allows researchers to publish the narrative, but also share narratives or reuse other people’s narratives. The interactive presentation of a narrative is complementary to the presentation in a text, but it can serve as a starting point for further exploration of other researchers who make use of the DIVE browser.
Within DIVE and Clariah, we are currently extending the user interface based on the recommendations made in the context of this thesis. You can read more about it in Maartje Kruijt’s thesis (Dutch). The user stories that describe the needs of media researchers are descibed in English and found in Appendix I.
[This post describes Aschwin Stacia‘s MSc. project and is based on his thesis]
There are many online and private film collections that lack structured annotations to facilitate retrieval. In his Master project work, Aschwin Stacia explored the effectiveness of a crowd-and nichesourced film tagging platform, around a subset of the Eye Open Beelden film collection.
Specifically, the project aimed at soliciting annotations appropriate for various types of media scholars who each have their own information needs. Based on previous research and interviews, a framework categorizing these needs was developed. Based on this framework a data model was developed that matches the needs for provenance and trust of user-provided metadata.
A crowdsourcing and retrieval platform (FilmTagging) was developed based on this framework and data model. The frontend of the platform allows users to self-declare knowledge levels in different aspects of film and also annotate (describe) films. They can also use the provided tags and provenance information for retrieval and extract this data from the platform.
To test the effectiveness of platform Aschwin conducted an experiment in which 37 participants used the platform to make annotations (in total, 319 such annotations were made). The figure below shows the average self-reported knowledge levels.
The annotations and the platform were then positively evaluated by media scholars as it could provide them with annotations that directly lead to film fragments that are useful for their research activities.
Nevertheless, capturing every scholar’s specific information needs is hard since the needs vary heavily depending on the research questions these scholars have.
[This post by Julia Salomons describes her Computer Science Master project]
‘Communication is key’ a phrase known worldwide, it is how people exchange ideas, knowledge, feelings, thoughts and much more. Communication between people comes in all different forms: verbal, visual or electronic to name a few. For many choosing which form of communication they wish to communicate in is an option. However, when someone suffers from hearing loss they tend to lose the option to choose.
Depending where you are in the world, the support and care that is available to those who are deaf can vary greatly. In developing regions such as Sub-Saharan Africa (SSA) the support and care varies within the region, from acceptance to rejection. Where on one end of the spectrum, acceptance, individuals are allowed to express themselves how they want whereas on the other end individuals are trapped in their environment. Where some cases they fear for their lives.
The problem that was uncovered during our research showed us that there was a lack of communication between hearing and deaf individuals. Deaf individuals who were lucky enough to attend school or gain support from the government or organisations, learned how to communicate through sign language. However, even with the ability to communicate the communication with other deaf individuals is where the communication stops, which increases the gap between deaf and hearing individuals. This project focused on decreasing that gap, by creating an educational mobile application, Learn to Sign, which would assist hearing individuals learn sign language.
[This post is based on the Information Sciences MSc. thesis by Onno Valkering]
To make widespread knowledge sharing possible in rural areas in developing countries, the notion of the Web has to be downscaled based on the specific low-resource infrastructure in place. In this paper, we introduce SPARQL over SMS, a solution for exchanging RDF data in which HTTP is substituted by SMS to enable Web-like exchange of data over cellular networks.
The solution uses converters that take outgoing SPARQL queries sent over HTTP and convert them into SMS messages sent to phone numbers (see architecture image). On the receiver-side, the messages are converted back to standard SPARQL requests.
The converters use various data compression strategies to ensure optimal use of the SMS bandwidth. These include both zip-based compression and the removal of redundant data through the use of common background vocabularies. The thesis presents the design and implementation of the solution, along with evaluations of the different data compression methods.
The application is validated in two real-world ICT for Development (ICT4D) cases that both use the Kasadaka platform: 1) An extension of the DigiVet application allows sending information related to veterinary symptoms and diagnoses accross different distributed systems. 2) An extension of the RadioMarche applicationinvolves the retrieval and adding of current offerings in the market information system, including the phone number of the advertisers.
For more information:
Download Onno’s Thesis. A version of the thesis is currently under review.
[This post is based on Andre Baart’s B.Sc. thesis. The text is mostly written by him]
In developing (rural) communities, the adoption of mobile phones is widespread. This allows information to be offered to these communities through voice-based services. This research explores the possibilities of creating a flexible framework (Kasadaka) for hosting voice services in rural communities. The context of the developing world poses special requirements, which have been taken into account in this research. The framework creates a voice service that incorporates dynamic data from a data store. The framework allows for a low-effort adaptation to new and changing use cases. The service is hosted on cheap, low-powered hardware and is connected to the local GSM network through a dongle. We validated the working and flexibility of the framework by adapting it to a new use case. Setting up this new voice server was possible in less than one hour, proving that it is suitable for rapid prototyping. This framework enables further research into the effects and possibilities of hosting voice based information services in the developing world. The image below shows the different components and the dataflow between these components when a call is made. Read more in Andre Baart‘s thesis (pdf).
All information on how to get started with Kasadaka can be found on the project’s GitHub page: https://github.com/abaart/KasaDaka
Text in italics only takes place when setting up the call.
Asterisk receives the call from the GSM dongle, answers the call, and connects it to VXI. Asterisk receives the user’s input and forwards it to VXI.
VXI requests the configured VoiceXML document from Apache. VXI requests the configured VoiceXML document from Apache. Together with the request, it sends the user input.
Apache runs the Python program (based on Flask), in which data from the triple store has to be read or written. Python sends the SPARQL query to ClioPatria.
ClioPatria runs the query on the data present, and sends the result of the query back to the Python program.
Python renders the VoiceXML template. The dynamic data is now inserted in the VoiceXML document, and it is sent back to VXI.
VXI starts interpreting the VoiceXML document. In the document there are references to audio files. It sends requests to Apache for the referenced files.
Apache sends a request for the file to the file system.
The file is read from the file system.
Apache responds with the requested audio files.
VXI puts all the audio files in the correct order and plays them back sequentially, sending the audio to the GSM dongle.