AT&T Labs

About: AT&T Labs is a based out in . It is known for research contribution in the topics: Network packet & The Internet. The organization has 1879 authors who have published 5595 publications receiving 483151 citations.

DPT: differentially private trajectory synthesis using hierarchical reference systems

Abstract: GPS-enabled devices are now ubiquitous, from airplanes and cars to smartphones and wearable technology. This has resulted in a wealth of data about the movements of individuals and populations, which can be analyzed for useful information to aid in city and traffic planning, disaster preparedness and so on. However, the places that people go can disclose extremely sensitive information about them, and thus their use needs to be filtered through privacy preserving mechanisms. This turns out to be a highly challenging task: raw trajectories are highly detailed, and typically no pair is alike. Previous attempts fail either to provide adequate privacy protection, or to remain sufficiently faithful to the original behavior.This paper presents DPT, a system to synthesize mobility data based on raw GPS trajectories of individuals while ensuring strong privacy protection in the form of e-differential privacy. DPT makes a number of novel modeling and algorithmic contributions including (i) discretization of raw trajectories using hierarchical reference systems (at multiple resolutions) to capture individual movements at differing speeds, (ii) adaptive mechanisms to select a small set of reference systems and construct prefix tree counts privately, and (iii) use of direction-weighted sampling for improved utility. While there have been prior attempts to solve the subproblems required to generate synthetic trajectories, to the best of our knowledge, ours is the first system that provides an end-to-end solution. We show the efficacy of our synthetic trajectory generation system using an extensive empirical evaluation.

An image transform approach for HMM based automatic lipreading

Abstract: This paper concentrates on the visual front end for hidden Markov model based automatic lipreading. Two approaches for extracting features relevant to lipreading, given image sequences of the speaker's mouth region, are considered: a lip contour based feature approach which first obtains estimates of the speaker's lip contours and subsequently extracts features from them; and an image transform based approach, which obtains a compressed representation of the image pixel values that contain the speaker's mouth. Various possible features are considered in each approach, and experimental results on a number of visual-only recognition tasks are reported. It is shown that the image transform based approach results in superior lipreading performance. In addition, feature mean subtraction is demonstrated to improve the performance in multi-speaker and speaker-independent recognition tasks. Finally, the effects of video degradations to image transform based automatic lipreading are studied. It is shown that lipreading performance dramatically deteriorates below a 10 Hz field rate, and that image transform features are robust to noise and compression artifacts.

Efficient biased sampling for approximate clustering and outlier detection in large data sets

Abstract: We investigate the use of biased sampling according to the density of the data set to speed up the operation of general data mining tasks, such as clustering and outlier detection in large multidimensional data sets. In density-biased sampling, the probability that a given point will be included in the sample depends on the local density of the data set. We propose a general technique for density-biased sampling that can factor in user requirements to sample for properties of interest and can be tuned for specific data mining tasks. This allows great flexibility and improved accuracy of the results over simple random sampling. We describe our approach in detail, we analytically evaluate it, and show how it can be optimized for approximate clustering and outlier detection. Finally, we present a thorough experimental evaluation of the proposed method, applying density-biased sampling on real and synthetic data sets, and employing clustering and outlier detection algorithms, thus highlighting the utility of our approach.

Visual prosody: facial movements accompanying speech

Abstract: As we articulate speech, we usually move the head and exhibit various facial expressions. This visual aspect of speech aids understanding and helps communicating additional information, such as the speaker's mood. We analyze quantitatively head and facial movements that accompany speech and investigate how they relate to the text's prosodic structure. We recorded several hours of speech and measured the locations of the speakers' main facial features as well as their head poses. The text was evaluated with a prosody prediction tool, identifying phrase boundaries and pitch accents. Characteristic for most speakers are simple motion patterns that are repeatedly applied in synchrony with the main prosodic events. Direction and strength of head movements vary widely from one speaker to another, yet their timing is typically well synchronized with the spoken text. Understanding quantitatively the correlations between head movements and spoken text is important for synthesizing photo-realistic talking heads. Talking heads appear much more engaging when they exhibit realistic motion patterns.

TTT plots: a perl program to create time-to-target plots

Abstract: This paper describes a perl language program to create time-to-target solution value plots for measured CPU times that are assumed to fit a shifted exponential distribution. This is often the case in local search based heuristics for combinatorial optimization, such as simulated annealing, genetic algorithms, iterated local search, tabu search, WalkSAT, and GRASP. Such plots are very useful in the comparison of different algorithms or strategies for solving a given problem and have been widely used as a tool for algorithm design and comparison. We first discuss how TTT plots are generated. This is followed by a description of the perl program tttplots.pl.