UNT Theses and Dissertations - 2 Matching Results

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Automatic Speech Recognition Using Finite Inductive Sequences

Description: This dissertation addresses the general problem of recognition of acoustic signals which may be derived from speech, sonar, or acoustic phenomena. The specific problem of recognizing speech is the main focus of this research. The intention is to design a recognition system for a definite number of discrete words. For this purpose specifically, eight isolated words from the T1MIT database are selected. Four medium length words "greasy," "dark," "wash," and "water" are used. In addition, four short words are considered "she," "had," "in," and "all." The recognition system addresses the following issues: filtering or preprocessing, training, and decision-making. The preprocessing phase uses linear predictive coding of order 12. Following the filtering process, a vector quantization method is used to further reduce the input data and generate a finite inductive sequence of symbols representative of each input signal. The sequences generated by the vector quantization process of the same word are factored, and a single ruling or reference template is generated and stored in a codebook. This system introduces a new modeling technique which relies heavily on the basic concept that all finite sequences are finitely inductive. This technique is used in the training stage. In order to accommodate the variabilities in speech, the training is performed casualty, and a large number of training speakers is used from eight different dialect regions. Hence, a speaker independent recognition system is realized. The matching process compares the incoming speech with each of the templates stored, and a closeness ration is computed. A ratio table is generated anH the matching word that corresponds to the smallest ratio (i.e. indicating that the ruling has removed most of the symbols) is selected. Promising results were obtained for isolated words, and the recognition rates ranged between 50% and 100%.
Date: August 1996
Creator: Cherri, Mona Youssef, 1956-
Partner: UNT Libraries

Practical Parallel Processing

Description: The physical limitations of uniprocessors and the real-time requirements of numerous practical applications have made parallel processing an essential technology in military, industry and scientific research. In this dissertation, we investigate parallelizations of three practical applications using three parallel machine models. The algorithms are: Finitely inductive (FI) sequence processing is a pattern recognition technique used in many fields. We first propose four parallel FI algorithms on the EREW PRAM. The time complexity of the parallel factoring and following by bucket packing is O(sk^2 n/p), and they are optimal under some conditions. The parallel factoring and following by hashing requires O(sk^2 n/p) time when uniform hash functions are used and log(p) ≤ k n/p and pm ≈ n. Their speedup is proportional to the number processors used. For these results, s is the number of levels, k is the size of the antecedents and n is the length of the input sequence and p is the number of processors. We also describe algorithms for raster/vector conversion based on the scan model to handle block-like connected components of arbitrary geometrical shapes with multi-level nested dough nuts for the IES (image exploitation system). Both the parallel raster-to-vector algorithm and parallel vector-to-raster algorithm require O(log(n2)) or O(log2(n2)) time (depending on the sorting algorithms used) for images of size n2 using p = n2 processors. Not only is the DWT (discrete wavelet transforms) useful in data compression, but also has it potentials in signal processing, image processing, and graphics. Therefore, it is of great importance to investigate efficient parallelizations of the wavelet transforms. The time complexity of the parallel forward DWT on the parallel virtual machine with linear processor organization is O(((so+s1)mn)/p), where s0 and s1 are the lengths of the filters and p is the number of processors used. The time complexity of the ...
Date: August 1996
Creator: Zhang, Hua, 1954-
Partner: UNT Libraries