International Institute of Information Technology, Hyderabad

About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Authentication & Internet security. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).

Panoramic Stereo Videos with a Single Camera

Abstract: We present a practical solution for generating 360° stereo panoramic videos using a single camera. Current approaches either use a moving camera that captures multiple images of a scene, which are then stitched together to form the final panorama, or use multiple cameras that are synchronized. A moving camera limits the solution to static scenes, while multi-camera solutions require dedicated calibrated setups. Our approach improves upon the existing solutions in two significant ways: It solves the problem using a single camera, thus minimizing the calibration problem and providing us the ability to convert any digital camera into a panoramic stereo capture device. It captures all the light rays required for stereo panoramas in a single frame using a compact custom designed mirror, thus making the design practical to manufacture and easier to use. We analyze several properties of the design as well as present panoramic stereo and depth estimation results.

Acoustic analysis of trill sounds

Abstract: In this paper, the acoustic–phonetic characteristics of steady apical trills—trill sounds produced by the periodic vibration of the apex of the tongue—are studied. Signal processing methods, namely, zero-frequency filtering and zero-time liftering of speech signals, are used to analyze the excitation source and the resonance characteristics of the vocal tract system, respectively. Although it is natural to expect the effect of trilling on the resonances of the vocal tract system, it is interesting to note that trilling influences the glottal source of excitation as well. The excitation characteristics derived using zero-frequency filtering of speech signals are glottal epochs, strength of impulses at the glottal epochs, and instantaneous fundamental frequency of the glottal vibration. Analysis based on zero-time liftering of speech signals is used to study the dynamic resonance characteristics of vocal tract system during the production of trill sounds. Qualitative analysis of trill sounds in different vo...

Resource Creation Towards Automated Sentiment Analysis in Telugu (a low resource language) and Integrating Multiple Domain Sources to Enhance Sentiment Prediction.

Abstract: Understanding the polarity or sentiment of a text is an important task in many application scenarios. Sentiment Analysis of a text can be used to answer various questions such as election prediction, favouredness towards any product etc. But the sentiment analysis task becomes challenging when it comes to low resource languages because the basis of learning sentiment classifiers are annotated datasets and annotated datasets for non-English texts hardly exists. So for the development of sentiment classifiers in Telugu, we have created corpora "Sentiraama" for different domains like movie reviews, song lyrics, product reviews and book reviews in Telugu language with the text written in Telugu script. In this paper, we describe the process of creating the corpora and assigning polarities to them. After the creation of corpora, we trained the classifiers that yields good classification results. Typically a sentiment classifier is trained using data from the same domain it is intended to be tested on. But there may not be sufficient data available in the same domain and additionally using data from multiple sources and domains may help in creating a more generalized sentiment classifier which can be applied to multiple domains. So to create this generalized classifier, we used the sentiment data from the above corpus from different domains. We first tested the performance of sentiment analysis models built using single data source for both in-domain and cross-domain classification. Later, we built sentiment model using data samples from multiple domains and then tested the performance of the models based on their classification. Finally, we compared all the three approaches based on the performance of the models and discussed the best approach for sentiment analysis.

Towards Interpretation of Node Embeddings

Abstract: Recently there have been a large number of studies on embedding large-scale information networks using low-dimensional, neighborhood and community aware node representations. Though the performance of these embedding models have been better than traditional methods for graph mining applications, little is known about what these representations encode, or why a particular node representation works better for certain tasks. Our work presented here constitutes the first step in decoding the black-box of vector embeddings of nodes by evaluating their effectiveness in encoding elementary properties of a node such as page rank, degree, closeness centrality, clustering coefficient, etc. We believe that a node representation is effective for an application only if it encodes the application-specific elementary properties of nodes. To unpack the elementary properties encoded in a node representation, we evaluate the representations on the accuracy with which they can model each of these properties. Our extensive study of three state-of-the-art node representation models (DeepWalk, node2vec and LINE) on four different tasks and six diverse graphs reveal that node2vec and LINE best encode the network properties of sparse and dense graphs respectively. We correlate the model performance obtained for elementary property prediction tasks with the high-level downstream applications such as link prediction and node classification, and visualize the task performance vector of each model to understand the semantic similarity between the embeddings learned by various models. Our first study of the node embedding models for outlier detection reveals that node2vec and DeepWalk identify outliers well for sparse and dense graphs respectively. Our analysis highlights that the proposed elementary property prediction tasks help in unearthing the important features responsible for the given node embedding model to perform well for a given downstream task. This understanding would facilitate in picking the right model for a given downstream task.

On Minimal Connectivity Requirement for Secure Message Transmission in Asynchronous Networks

Abstract: In the PSMT problem, a sender S and a receiver R are part of a distributed network and connected through n node disjoint paths, also called as wires among which at most t are controlled by an all powerful Byzantine adversary ${\mathcal{A}_t}$. S has a message m , which S intends to send to R. The challenge is to design a protocol, such that at the end, R should correctly output m without any error (perfect reliability) and ${\mathcal{A}_t}$ should not get any information about m , what so ever, in information theoretic sense (perfect security). The problem of USMT is same as PSMT, except that R should output m with a small probability of error. Sayeed et al. [15] have given a PSMT protocol in an asynchronous network tolerating ${\mathcal A}_t$, where S and R are connected by n = 2t + 1 wires. However, we show that their protocol does not provide perfect security. We then prove that in an asynchronous network, if all the n wires are directed from S to R, then any PSMT protocol tolerating ${\mathcal{A}_t}$ is possible iff n > 3t . Surprisingly, we further prove that even if all the n wires are bi-directional, then any PSMT protocol in asynchronous network tolerating ${\mathcal{A}_t}$ is possible iff n > 3t . This is quite interesting because for synchronous networks, by the results of Dolev et al. [6] , if all the wires are unidirectional (directed from S to R), then PSMT tolerating ${\mathcal{A}_t}$ is possible iff n > 3t , where as if all the wires are bi-directional then PSMT tolerating ${\mathcal{A}_t}$ is possible iff n > 2t . This shows that synchrony of the network affects the connectivity requirement for PSMT protocols. However, we show that n > 2t wires are necessary and sufficient for the existence of any USMT protocol in asynchronous network tolerating ${\mathcal{A}_t}$, irrespective of whether the n wires are unidirectional from S to R or the n wires are bi-directional.