There has been a fair amount of work on automatic speech translation systems that translate in real-time, serving as a computerized version of a simultaneous interpreter. It has been noticed in the field of translation studies that simultaneous interpreters perform a number of tricks to make the content easier to understand in real-time, including dividing their translations into small chunks, ...

We study the effect of Explicit Congestion Notification on TCP performance for two simultaneous large file transfers. We compare this performance with that achieved using other congestion avoidance mechanisms, namely Drop Tail and RED. Our results show that TCP performance improves, in certain cases significantly, with ECN both for individual flows and the network as a whole.

Recognizing speech in adverse listening conditions is a significant cognitive, perceptual, and linguistic challenge, especially for children. Prior studies have yielded mixed results on the impact of bilingualism on speech perception in noise. Methodological variations across studies make it difficult to converge on a conclusion regarding the effect of bilingualism on speech-in-noise performanc...

Power consumption has become an increasing concern in high performance microprocessor design in terms of packaging and cooling cost. The fetch unit including instruction cache contributes a large portion of the total power consumption in the microprocessor. The instruction cache itself suffers some hidden power consumption due to dynamic control flows. Although capturing the dynamic control flo...

As technology advances, microprocessors that support multiple threads of execution on a single chip are becoming increasingly common. Improving the performance of general purpose applications by extracting parallel threads is extremely difficult, due to the complex control flow and ambiguous data dependences that are inherent to these applications. Thread-Level Speculation (TLS) enables specula...

In Robotics, especially in this era of autonomous driving, mapping is one key ability of a robot to be able to navigate through an environment, localize on it and analyze its traversability. To allow for real-time execution on constrained hardware, the map usually estimated by feature-based or semidense SLAM algorithms is a sparse point cloud; a richer and more complete representation of the en...

The principle behind VSLAM applications like 3D object reconstruction or indoor mapping is to estimate the spatial transformation between two large clouds of points, which represent two poses of the same scene. They can further be processed to obtain detailed surfaces. Since its introduction in 1992, the standard algorithm for finding the alignment between two point cloud...

The basis for most vision based applications like robotics, self-driving cars and potentially augmented and virtual reality is a robust, continuous estimation of the position and orientation of a camera system w.r.t the observed environment (scene). In recent years many vision based systems that perform simultaneous localization and mapping (SLAM) have been presented and released as open source...

Often Particle Filters are used to solve the SLAM (Simultaneous Localization and Mapping) problem in robotics: The particles represent the possible poses of the robot, and their weight is determined by checking if the sensor readings are consistent with the so far acquired map. Mostly a single map is maintained during the exploration, and only with Rao-Blackwellized Particle Filters each partic...