413264
Phonetic Speaker Recognition with Support Vector Machines
A recent area of significant progress in speaker recognition is the use of high level features—idiolect, phonetic relations, prosody, discourse structure, etc. A speaker not only has a distinctive acoustic sound but uses language in a characteristic manner. Large corpora of speech data available in recent years allow experimentation with long term statistics of phone patterns, word patterns, etc. of an individual. We propose the use of support vector machines and term frequency analysis of phone sequences to model a given speaker. To this end, we explore techniques for text categorization applied to the problem. We derive a new kernel based upon a linearization of likelihood ratio scoring. We introduce a new phone-based SVM speaker recognition approach that halves the error rate of conventional phone-based approaches.
12160909
An Architecture For A Universal Lexicon: A Case Study on Shared Syntactic Information in Japanese, Hindi, Bengali, Greek, and English
Naoyuki Nomura, Douglas A. Jones, Robert C. Berwick Massachusetts Institute of Technology, NE43-802 Artificial Intelligence Laboratory nomura@ai.mit.edu Introduction. Given the prominence of the lexicon in most current linguistic theories (LFG, HPSG, GB), the inventory of language particular information left in the lexicon deserves special attention. Constructing large computerized lexicons remains a difficult problem, building a large array of apparently arbitrary information. This paper shows that this arbitrariness can be constrained more than might have been previously thought. In particular, arbitrariness of argument structure, word sense, and paraphrasability will be shown not only to be constrained, but also to be integrally related. Our (radical) view is that variation of lexical behavior across languages is exactly like lexical variation within languages, specifically, the difference lies in the presence or absence of certain morphemes. For example, the fact that Japanese has richer possibilities in certain verbal patterns is derived solely from its morphological inventory.1 Put another way, language parameters simply are the presence or absence of lexical material in the morphological component. Observed language variation patterns reflect morphological systematicity. The generative machinery for producing argument structure positions is fixed across languages. Linguistic Motivation. A striking example underscoring universality of argument structure is the familiar Spray/Load alternation2, shown in (1). Despite the many surface differences in these data across languages, they share several essential properties. (1) a. b. John loaded the hay on the wagon. John loaded the wagon with the hay. Japanese (2) a. taroo-wa teepu-o boo-ni maita. Taro-NOM tape-ACC stick-DAT wrap-PRF 'Taro wrapped the tape around the stick.'
9402109
Toward a Scoring Function for Quality-Driven Machine Translation
We describe how we constructed an automatic scoring function for machine translation quality; this function makes use of arbitrarily many pieces of natural language processing software that has been designed to process English language text. By machine-learning values of functions available inside the software and by constructing functions that yield values based upon the software output, we are able to achieve preliminary, positive results in machine-learning the difference between human-produced English and machine-translation English. We suggest how the scoring function may be used for MT system development.
16917081
Role of Word Sense Disambiguation in Lexical Acquisition: Predicting Semantics from Syntactic Cues
This paper addresses the issue of word-sense ambiguity in extraction from machine-readable resources for the construction of large-scale knowledge sources. We describe two experiments: one which ignored word-sense distinctions, resulting in 6.3% accuracy for semantic classification of verbs based on (Levin, 1993); and one which exploited word-sense distinctions, resulting in 97.9% accuracy. These experiments were dual purpose: (1) to validate the central thesis of the work of (Levin, 1993), i.e., that verb semantics and syntactic behavior are predictably related; (2) to demonstrate that a 15-fold improvement can be achieved in deriving semantic information from syntactic cues if we first divide the syntactic cues into distinct groupings that correlate with different word senses. Finally, we show that we can provide effective acquisition techniques for novel word senses using a combination of online sources.
6816511
Joint source channel matching for a wireless communications link
Summary form only given. With the rapid growth of wireless communications systems there is an increasing demand for efficient image and video transmission. Significant performance gains can be obtained from joint source channel matching where system resources are assigned based on the tradeoff between data and redundancy. We develop a more general approach for joint source channel matching based on a parametric distortion model that incorporates the flexibility and constraints of both the source and the channel. We use parametric models describing source and channel. We use parametric models describing source and channel characteristics that can be accurately applied to most classes of source and channel coders. To show the generality of our approach, we applied it to the familiar Said-Pearlman progressive image coder with two types of channel coders, a coder with orthogonal symbols of different power, and fixed-rate BPSK modulation overlaid with Reed Solomon codes.
14721450
Implementation of a block based neural branch predictor
This paper contributes to a dynamic branch predictor algorithm based on a perceptron in two directions: Firstly, a new block form of computation is introduced that reduces theoretically by half the combinational critical path for computing a prediction. Secondly, implementation in FPGA hardware is fully developed for quantitative comparison purposes. FPGA circuits for a one-cycle block predictor produces 1.7 faster clock rates than a direct implementation of the original perceptron predictor. This faster clock allows to realize predictions with longer history lengths for the same hardware budget.
31768671
Protein fold recognition
SummaryAn important, yet seemingly unattainable, goal in structural molecular biology is to be able to predict the native three-dimensional structure of a protein entirely from its amino acid sequence. Prediction methods based on rigorous energy calculations have not yet been successful, and best results have been obtained from homology modelling and statistical secondary structure prediction. Homology modelling is limited to cases where significant sequence similarity is shared between a protein of known structure and the unknown. Secondary structure prediction methods are not only unreliable, but also do not offer any obvious route to the full tertiary structure. Recently, methods have been developed whereby entire protein folds are recognized from sequence, even where little or no sequence similarity is shared between the proteins under consideration. In this paper we review the current methods, including our own, and in particular offer a historical background to their development. In addition, we also discuss the future of these methods and outline the developments under investigation in our laboratory.
6177362
Line and boundary detection in speckle images
This paper considers the problem of detecting lines in speckle imagery, such as that produced by synthetic aperture radar (SAR) or ultrasound techniques. Using the physical principles that account for the speckle phenomenon, we derive the optimal detector for lines in fully developed speckle, and we compare the optimal detector to several suboptimal detection rules that are more computationally efficient. We show that when the noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance. Finally, we also discuss the application of this technique to medical ultrasonic images, where the detection of tissue boundaries is considered as a problem of line detection.
17269099
Edge detection in ultrasound speckle noise
Presents a statistical approach to edge detection in ultrasound speckle, and uses actual noise statistics to derive an expression for an optimal detection rule. The authors compute the optimal detector for the special case of uncorrelated speckle, and an approximation to the optimal detector for the case when signal-to-noise ratio (SNR) is high. They also discuss a simple sub-optimal detection scheme, and show that its performance is close to that of the optimal uncorrelated speckle detection rule, and surpasses that of the high-SNR approximation except in the case of extremely high SNR, in which case they both perform equally well.<<ETX>>