26885251
Automatic Recognition of Birdsongs Using Mel-frequency Cepstral Coefficients and Vector Quantization
3020567
Automatic recognition of animal vocalizations using averaged MFCC and linear discriminant analysis
In this paper we propose a method that uses the averaged Mel-frequency cepstral coefficients (MFCCs) and linear discriminant analysis (LDA) to automatically identify animals from their sounds. First, each syllable corresponding to a piece of vocalization is segmented. The averaged MFCCs over all frames in a syllable are calculated as the vocalization features. Linear discriminant analysis (LDA), which finds out a transformation matrix that minimizes the within-class distance and maximizes the between-class distance, is utilized to increase the classification accuracy while to reduce the dimensionality of the feature vectors. In our experiment, the average classification accuracy is 96.8% and 98.1% for 30 kinds of frog calls and 19 kinds of cricket calls, respectively.
34408109
Modeling GIS Data Using OMEGA
558748
Speech through myoelectric signal recognition SMyLES
People who can not communicate throu­ gh audible speech are separated from society. SMyLES, MES hardware, and Speech generation hardware will allow these people the ability to join society. This paper is about the software called SMyLES that is the heart of the speecli recognition through myoelectric
1626827
Augmenting kitchen appliances with a shared context using knowledge about daily events
Networked appliances might make them aware of each other, but interacting with a complex network can be difficult in itself. KitchenSense is a sensor rich networked kitchen research platform that uses Common Sense reasoning to simplify control interfaces and augment interaction. The system's sensor net attempts to interpret people's intentions to create fail-soft support for safe, efficient and aesthetic activity. By considering embedded sensor data together with daily-event knowledge, a centrally-controlled system can develop a shared context across various appliances. The system is a research platform that is used to evaluate augmented intelligent support of work scenarios in physical spaces.
1423815
Simple vector microprocessors for multimedia applications
In anticipation of the emergence of multimedia applications as an important workload, microprocessor companies have augmented their instruction-set architectures with short vector extensions, thus adding basic vector hardware to state-of-the-art superscalar processors. Although a vector architecture may be a good match for multimedia applications, there is growing evidence that the control logic for increasingly complex superscalar processors is difficult to implement, Rather than combining a complex superscalar core with short wide vector hardware, we propose using a much simpler processor design that is similar to traditional vector computers with long vectors and simple control logic for instruction issue. Such a design would use the bulk of its transistors and die area for datapath and registers, and thus lessen the time required to design, implement, and verify control. In this paper we present data that quantifies this trading of control transistors for datapath and register transistors. We demonstrate that a 2-way, in-order vector processor with a vector length of 64 and a vector width of 8 requires no more die area, and possibly significantly less area, than a 4-way, out-of-order superscalar processor with short vector extensions. Furthermore, we show that the simple long vector processor is, on average, 2.7 times faster executing multimedia applications than the superscalar processor; and 1.6 times faster than one with short vector extensions. To explain the reasons for the higher performance, we analyze execution time in terms of dynamic operation count and cycles per operation (CPO). A vector processor executes fewer operations by using vector instructions to stripmine a loop. Moreover, a long vector processor achieves a lower CPO by effectively using parallelism at both the operation and the instruction levels. Thus by reducing both terms of the CPO equation, the simple long vector processor achieves greater performance.
9639915
Support for adaptivity in ARMCI using migratable objects
Many new paradigms of parallel programming have emerged that compete with and complement the standard and well-established MPI model. Most notable, and successful, among these are models that support some form of global address space. At the same time, approaches based on migratable objects (also called virtualized processes) have shown that resource management concerns can be separated effectively from the overall parallel programming effort. For example, Charm++ supports dynamic load balancing via an intelligent adaptive run-time system. It is also becoming clear that a multi-paradigm approach that allows modules written in one or more paradigms to coexist and co-operate will be necessary to tame the parallel programming challenge. ARMCI is a remote memory copy library that serves as a foundation of many global address space languages and libraries. This paper presents our preliminary work on integrating and supporting ARMCI with the adaptive run-time system of Charm++ as a part of our overall effort in the multi-paradigm approach