Lexical Effects in Perception of Tamil Geminates

Lexical status effects are a phenomenon in which listeners use their prior lexical knowledge of a language to identify ambiguous speech sounds in a word based on its word or nonword status. This phenomenon has been demonstrated for ambiguous initial English consonants (one example being the Ganong Effect, a phenomenon in which listeners perceive an ambiguous speech sound as a phoneme that would complete a real word rather than a nonsense word) as a supporting factor for top-down lexical processing affecting listeners' subsequent acoustic judgement, but not for ambiguous mid-word consonants in non-English languages. In this experiment, we attempt to look at ambiguous mid-word consonants with Tamil, a South Asian language in order to see if the same top-down lexical effect was applicable outside of English. These Tamil consonants can present as either singletons (single speech sounds) or geminates (doubled speech sounds).We hypothesized that by creating ambiguous stimuli between a geminate word kuppam and a singleton non-word like kubam, participants would be more likely to perceive the ambiguous sound as a phoneme that completes the real word rather than the nonword (in this case, perceiving the ambiguous sound as a /p/ for kuppam instead of kubam). Participants listened to the ambiguous stimuli in two separate sets of continua (kuppam/suppam and nakkam/pakkam) and then indicated which word they heard in a four-alternative forced choice word identification task. Results showed that participants identified the ambiguous sounds as the sound that completed the actual word, but only for one set of continua (kuppam/suppam). These data suggest that there may be strong top-down lexical effects for ambiguous sounds in certain stimuli in Tamil, but not others.No embargoAcademic Major: LinguisticsAcademic Major: Psycholog

Designing labeled graph classifiers by exploiting the R\'enyi entropy of the dissimilarity representation

Representing patterns as labeled graphs is becoming increasingly common in the broad field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools, such as classifiers and knowledge discovery procedures, are nowadays available and tested for various datasets of labeled graphs. However, the design of effective learning procedures operating in the space of labeled graphs is still a challenging problem, especially from the computational complexity viewpoint. In this paper, we present a major improvement of a general-purpose classifier for graphs, which is conceived on an interplay between dissimilarity representation, clustering, information-theoretic techniques, and evolutionary optimization algorithms. The improvement focuses on a specific key subroutine devised to compress the input data. We prove different theorems which are fundamental to the setting of the parameters controlling such a compression operation. We demonstrate the effectiveness of the resulting classifier by benchmarking the developed variants on well-known datasets of labeled graphs, considering as distinct performance indicators the classification accuracy, computing time, and parsimony in terms of structural complexity of the synthesized classification models. The results show state-of-the-art standards in terms of test set accuracy and a considerable speed-up for what concerns the computing time.Comment: Revised versio

Design of multimedia processor based on metric computation

Media-processing applications, such as signal processing, 2D and 3D graphics rendering, and image compression, are the dominant workloads in many embedded systems today. The real-time constraints of those media applications have taxing demands on today's processor performances with low cost, low power and reduced design delay. To satisfy those challenges, a fast and efficient strategy consists in upgrading a low cost general purpose processor core. This approach is based on the personalization of a general RISC processor core according the target multimedia application requirements. Thus, if the extra cost is justified, the general purpose processor GPP core can be enforced with instruction level coprocessors, coarse grain dedicated hardware, ad hoc memories or new GPP cores. In this way the final design solution is tailored to the application requirements. The proposed approach is based on three main steps: the first one is the analysis of the targeted application using efficient metrics. The second step is the selection of the appropriate architecture template according to the first step results and recommendations. The third step is the architecture generation. This approach is experimented using various image and video algorithms showing its feasibility

Global Thresholding and Multiple Pass Parsing

We present a variation on classic beam thresholding techniques that is up to an order of magnitude faster than the traditional method, at the same performance level. We also present a new thresholding technique, global thresholding, which, combined with the new beam thresholding, gives an additional factor of two improvement, and a novel technique, multiple pass parsing, that can be combined with the others to yield yet another 50% improvement. We use a new search algorithm to simultaneously optimize the thresholding parameters of the various algorithms.Comment: Fixed latex errors; fixed minor errors in published versio