Instructional videos are one of the most popular ways of teaching and learning in an online setting. However, navigation in videos is linear as compared to other instructional resources such as textbooks, where a table of topics and a multi-faceted index of different anchor points i.e., list of figures, tables aid in efficiently navigating to a desired point of interest. There is a lack of appropriate techniques and interfaces which can support such textbook-style navigation in instructional videos. This paper presents a novel approach to automatically localize and classify different anchor points in a video including figures, tables, equations, flowcharts, code snippets and charts. Our approach uses a deep convolution neural network in a semi-supervised fashion where the training data is obtained from the unconstrained Internet images. On an anchor point dataset of about 10K images, the proposed algorithm leads to a classification accuracy of 86%. Further, we designed a system ViZig that uses these localized anchor points along with a automatically generated list of topics for non-linear video navigation and studied its effectiveness in real-world. Our user studies with 18 participants establish that the proposed video navigation mechanism provides statistically significant time savings as compared to the popularly used time-synched transcript along with youtube-style timeline scrubbing.

The growth of Massive Open Online Courses (MOOCs) has been remarkable in the last few years. A significant amount of MOOCs content is in the form of videos and participants often use non-linear navigation to browse through a video. This paper proposes the design of a system that provides non-linear navigation in educational videos using features derived from a combination of audio and visual content of a video. It provides multiple dimensions for quickly navigating to a given point of interest in a video i.e., customized dynamic time-aware word-cloud, video pages, and a 2-D timeline. In word-cloud, the relative placement of the words indicates their temporal ordering in the video whereas color codes are used to represent acoustic stress. The 2-D timeline is used to present multiple occurrences of a keyword/concept in the video in response to user click in the word-cloud. Additionally, visual content is analyzed to identify frames with "maximum written content", known as video pages. We conducted a user study with 20 users to evaluate the proposed system and compared it with transcription-based interfaces used by major MOOC providers. Our findings suggest that the proposed system leads to statistically significant navigation time savings especially on multimodal navigation tasks.

MOOC participants spend most of their time watching videos in a course and recent studies have found that there is a requirement of non-linear navigation system for educational videos. We propose a system that provides efficient and non-linear navigation in a given video using multi-modal dimensions (i.e. customized word-cloud, image cloud) derived from video content. The end-to-end system is implemented and we demonstrate capabilities of proposed system using any given YouTube or MOOC video.

Heavy penetration of mobile devices in rural areas enables access to information services to low-literate users. While connectivity solves a major issue, concepts such as browsing and searching are not intuitive to such users. This paper presents the design of a multimodal (speech+icons) voice browser for low-literate users in rural India. We conducted a field study to determine their current communication styles and preferences. Based on this, we designed three browsers, each influenced by a specific way of communicating -- persona based roles, storytelling and direct interaction. The prototypes were evaluated in a task-based study with 62 low-literate users and were compared with a baseline Interactive Voice Response (IVR) browser. Our results suggest that there is clear acceptance and understanding of the necessary concepts if the browser is designed using the design constructs of persona based roles and storytelling.

Spoken Web is a web of VoiceSites that can be accessed by a phone. The content in a VoiceSite is audio. Therefore Spoken Web provides an alternate to the World Wide Web (WWW) in developing regions where low Internet penetration and low literacy are barriers to accessing the conventional WWW. Searching of audio content in Spoken Web through an audio query-result interface presents two key challenges: indexing of audio content is not accurate, and the presentation of results in audio is sequential, and therefore cumbersome. In this paper, we apply the concepts of faceted search and browsing to the SpokenWeb search problem. We use the concepts of facets to index the meta-data associated with the audio content. We provide a mechanism to rank the facets based on the search results. We develop an interactive query interface that enables easy browsing of search results through the top ranked facets. To our knowledge, this is the first system to use the concepts of facets in audio search, and the first solution that provides an audio search for the rural population.

Delivering new technology solutions in a well established IT-educated consumer market largely depends on the usefulness and usability of the solution. However, this is very different from delivering ICT solutions in developing regions where there are multiple factors that affect technology adoption, which seem to be at least as important as the technology itself. This paper revolves around a case study of World Wide Telecom Web (WWTW), commonly known as Spoken Web, a voice based content-creation and dissemination platform. The study reflects different challenges in adoption and different ways of evolution of WWTW in the varied organizational, social and operational settings in rural India. The case study uses pilot deployments in four regions in India, each involving at least 500 users. All the four deployments had a different organizational, social and operational model. This paper presents the implications of these differences on the WWTW technology adoption. The study shows that organizations have a strong influence in the adoption, social settings play a major role in the evolution of the solution and operational model influences the quality of the solution.

It is a common practice for us to skim textual content on a web page. While skimming, we usually skip words or phrases that are not of interest to us and we slow down our speed when the content seems to be of relevance to us. But when we listen to audio content, which is not persistent and is sequential, such skimming is not possible. In developing countries, cell-phone penetration is much higher than Internet penetration. Moreover, due to low literacy, voice is a convenient modality to access information. The skimming techniques are therefore more critical in the audio domain. In this paper, we describe the technique for navigating audio content while interacting with information systems in a client server environment, where a dumb phone is the client device. The paper presents techniques for skimming audio content and for placing markers in audio. The user studies conducted with 18 users for more than 1 month, in a live setting substantiates the usability and usefulness of the navigation techniques.