저작근 근전도에 관한 정상교합자와 ii급 부정교합자의 비교 연구

This paper develops an evaluation approach based on the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), to help the Air Force Academy in Taiwan choose optimal initial training aircraft in a fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterised by triangular fuzzy numbers. This study applies the fuzzy multi-criteria decision-making (MCDM) method to determine the importance weights of evaluation criteria and to synthesize the ratings of candidate aircraft. Aggregated the evaluators' attitude toward preference; then TOPSIS is employed to obtain a crisp overall performance value for each alternative to make a final decision. This approach is demonstrated with a real case study involving 16 evaluation criteria, seven initial propeller-driven training aircraft assessed by 15 evaluators from the Taiwan Air Force Academy.

http://p30bazar.persiangig.com/pdf/58.pdf

Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment

An effective multipitch tracking algorithm for noisy speech is critical for acoustic signal processing. However, the performance of existing algorithms is not satisfactory. We present a robust algorithm for multipitch tracking of noisy speech. Our approach integrates an improved channel and peak selection method, a new method for extracting periodicity information across different channels, and a hidden Markov model (HMM) for forming continuous pitch tracks. The resulting algorithm can reliably track single and double pitch tracks in a noisy environment. We suggest a pitch error measure for the multipitch situation. The proposed algorithm is evaluated on a database of speech utterances mixed with various types of interference. Quantitative comparisons show that our algorithm significantly outperforms existing ones.

/pdf/a-multipitch-tracking-algorithm-for-noisy-speech-3f4z4i5v9k.pdf

A multipitch tracking algorithm for noisy speech

In this paper, a fundamental frequency (F(0)) tracking algorithm is presented that is extremely robust for both high quality and telephone speech, at signal to noise ratios ranging from clean speech to very noisy speech. The algorithm is named "YAAPT," for "yet another algorithm for pitch tracking." The algorithm is based on a combination of time domain processing, using the normalized cross correlation, and frequency domain processing. Major steps include processing of the original acoustic signal and a nonlinearly processed version of the signal, the use of a new method for computing a modified autocorrelation function that incorporates information from multiple spectral harmonic peaks, peak picking to select multiple F(0) candidates and associated figures of merit, and extensive use of dynamic programming to find the "best" track among the multiple F(0) candidates. The algorithm was evaluated by using three databases and compared to three other published F(0) tracking algorithms by using both high quality and telephone speech for various noise conditions. For clean speech, the error rates obtained are comparable to those obtained with the best results reported for any other algorithm; for noisy telephone speech, the error rates obtained are lower than those obtained with other methods.

/pdf/a-spectral-temporal-method-for-robust-fundamental-frequency-4zlpypwr4b.pdf

A spectral/temporal method for robust fundamental frequency tracking

Fuzzy Logic for Embedded Systems Applications, by a recognized expert in the field, covers all the basic theory relevant to electronics design, with particular emphasis on embedded systems, and shows how the techniques can be applied to shorten design cycles and handle logic problems that are tough to solve using conventional linear techniques. All the latest advances in the field aree discussed and practical circuit design examples presented.Fuzzy logic has been found to be particularly suitable for many embedded control applications. The intuitive nature of the fuzzy-based system design saves engineers time and reduces costs by shortening product development cycles and making system maintenance and adjustments easier. Yet despite its wide acceptance—and perhaps because of its name—it is still misunderstood and feared by many engineers. There is a need for embedded systems designers—both hardware and software—to get up to speed on the principles and applications of fuzzy logic in order to ascertain when and how to use them appropriately.Fuzzy Logic for Embedded Systems Applications provides practical guidelines for designing electronic circuits and devices for embedded systems using fuzzy-based logic. It covers both theory and applications with design examples.

Fuzzy Logic for Embedded Systems Applications

In this paper, we propose a new scheme to analyze the spectral structure of speech signals for fundamental frequency estimation. First, we propose a pitch measure to detect the harmonic characteristics of voiced sounds on the spectrum of a speech signal. This measure utilizes the properties that there are distinct impulses located at the positions of fundamental frequency and its harmonics, and the energy of voiced sound is dominated by the energy of these distinct harmonic impulses. The spectrum can be obtained by the fast Fourier transform (FFT) however, it may be destroyed when the speech is interfered with by additive noise. To enhance the robustness of the proposed scheme in noisy environments, we apply the joint time-frequency analysis (JTFA) technique to obtain the adaptive representation of the spectrum of speech signals. The adaptive representation can accurately extract important harmonic structure of noisy speech signals at the expense of high computation cost. To solve this problem, we further propose a fast adaptive representation (FAR) algorithm, which reduces the computation complexity of the original algorithm by 50%. The performance of the proposed fundamental-frequency estimation scheme is evaluated on a large database with or without additive noise. The performance is compared to that of other approaches on the same database. The experimental results show that the proposed scheme performs well on clean speech and is robust in noisy environments.

https://ir.nctu.edu.tw:443/bitstream/11536/29402/1/000170651100001.pdf

Fundamental frequency estimation based on the joint time-frequency analysis of harmonic spectral structure

https://ir.nctu.edu.tw:443/bitstream/11536/28921/1/000174539100004.pdf

A neural fuzzy network for word information processing

Background noise added to speech can decrease the performance of speech segmentation and enhancement. To solve this problem, new methods have been developed in this thesis. First, a new speech segmentation method (ATF-based SONFIN algorithm) is proposed in fixed noise-level environment. This method contains the multiband analysis and a neural fuzzy network, and it achieves higher recognition rate than the TF-based robust algorithm by 5%. In addition, a new speech segmentation method called RTF-based RSONFIN algorithm is proposed for variable noise-level environment. The RTF-based RSONFIN algorithm contains a recurrent neural fuzzy network. This method contains the multiband analysis and achieve higher recognition rate than the TF-based robust algorithm by 12%.

/pdf/noisy-speech-segmentation-enhancement-with-multiband-2sr2hfeapx.pdf

Noisy Speech Segmentation/Enhancement with Multiband Analysis and Neural Fuzzy Networks

A novel programmable DSP core, called LASP24 (Low-cost Application-driven Speech Processor, with 24-bit data width), is developed. It is targeted as a wide-range platform of multimedia applications. The processor core is optimized to efficiently perform fundamental operations for speech/audio signal processing such as vector and matrix operations, and it can be easily embedded into the SOC platform. The design is fabricated with the UMC 0.18 m standard-cell technology in the total area of 6.5 mm2, and it can operate at 100 MHz. It has also been demonstrated that the MELP speech coding and the sound reverberation method could be executed in real-time on the LASP24 operating at 80 Mhz. The assembler and emulator environment have also been developed for designers to verify their algorithms.

/pdf/a-programmable-dsp-core-design-for-speech-audio-codec-soc-10onxnne.pdf

A programmable dsp core design for speech/audio codec soc

This paper proposes an innovative technique to incorporate the information of spectral dynamics into the line spectrum frequency (LSF) vector quantization (VQ). This technique is based on a modified weighted log-spectral distortion (MWLSD) measure. It can be used to shape the spectral quantization distortion distribution into any frequencydependent shaping curve, and simultaneously reduce the spectral dynamics distortion between quantized spectra and unquantized spectra. To reduce the high computational complexity of the MWLSD measure during the search procedure in the LSF VQ, a quadratically weighted distortion (QWD) measure used to approximate the MWLSD measure is derived based on the theoretical analysis of the MWLSD measure. A simplified quadratically weighted distortion (SQWD) measure is also proposed to further reduce the computational complexity of the QWD measure for practical applications, whose computational complexity is almost equal to that of weighted mean square error (WMSE) measure. Three experiments are performed to verify the proposed technique in the LSF VQ.

http://www.m-hikari.com/imf-password/5-8-2006/chungIMF5-8-2006.pdf

Der-Jenq Liu

Papers

Fundamental frequency estimation based on the joint time-frequency analysis of harmonic spectral structure

A neural fuzzy network for word information processing

Noisy Speech Segmentation/Enhancement with Multiband Analysis and Neural Fuzzy Networks

A programmable dsp core design for speech/audio codec soc

Incorporating Spectral Dynamics into LSF Vector Quantization with Error Shaping