Knowledge Transfer from Weakly Labeled Audio using Convolutional Neural Network for Sound Events and Scenes

In this work we propose approaches to effectively transfer knowledge from weakly labeled web audio data. We first describe a convolutional neural network (CNN) based framework for sound event detection and classification using weakly labeled audio data. Our model trains efficiently from audios of variable lengths; hence, it is well suited for transfer learning. We then propose methods to learn representations using this model which can be effectively used for solving the target task. We study both transductive and inductive transfer learning tasks, showing the effectiveness of our methods for both domain and task adaptation. We show that the learned representations using the proposed CNN model generalizes well enough to reach human level accuracy on ESC-50 sound events dataset and set state of art results on this dataset. We further use them for acoustic scene classification task and once again show that our proposed approaches suit well for this task as well. We also show that our methods are helpful in capturing semantic meanings and relations as well. Moreover, in this process we also set state-of-art results on Audioset dataset, relying on balanced training set.Comment: ICASSP 201

MIMO \u2798

Autonomous mobile robots have been present since the 1970\u27s. Some of these have evolved into maze solving robots presently known as a micromouse. Micromouse robots are gaining more popularity over the years. Micromouse competitions attract robotic fanatics from all over the world, old and young. MIMO \u2798 has also been bitten by the mouse mania happening abroad. MIMO \u2798 is a typical micromouse consisting of four subsystems namely the power, drive, sensor, and control system. Basically, a chassis was needed to support all the required features of a micromouse such as the body, wheels, motors, sensors, and the microcontroller. The wheels, motors, and motor driver circuits comprises the drive system. This system is responsible for the propulsion of the mouse. The sensor serves as the system\u27s eyes and gives input to help build a picture of the robot\u27s environment. For obvious reasons, the power is to supply the needed input voltage to turn on the system. Lastly, the microcontroller is considered as the heart of the system. It coordinates all the inputs from the different systems, process these inputs, and gives out the appropriate output signals. The mouse can think because of the maze-solving algorithm. The algorithm made use of the MC68HC11 instruction set. The program checks for walls from different directions and proceeds accordingly to the instructions coded. MIMO \u2798 can be considered as a first draft micromouse. It is working but it still needs a lot of improvement. Nevertheless, it serves as a good hands on tool for future robot designers and builders

Putting the Leishmania genome to work: functional genomics by transposon trapping and expression profiling.

Leishmania are important protozoan pathogens of humans in temperate and tropical regions. The study of gene expression during the infectious cycle, in mutants or after environmental or chemical stimuli, is a powerful approach towards understanding parasite virulence and the development of control measures. Like other trypanosomatids, Leishmania gene expression is mediated by a polycistronic transcriptional process that places increased emphasis on post-transcriptional regulatory mechanisms including RNA processing and protein translation. With the impending completion of the Leishmania genome, global approaches surveying mRNA and protein expression are now feasible. Our laboratory has developed the Drosophila transposon mariner as a tool for trapping Leishmania genes and studying their regulation in the form of protein fusions; a classic approach in other microbes that can be termed 'proteogenomics'. Similarly, we have developed reagents and approaches for the creation of DNA microarrays, which permit the measurement of RNA abundance across the parasite genome. Progress in these areas promises to greatly increase our understanding of global mechanisms of gene regulation at both mRNA and protein levels, and to lead to the identification of many candidate genes involved in virulence