No abstract

This brief presents a fixed-point architecture based on a reconfigurable scheme for integrating several commonly used mathematical operations of speech signal processing. The proposed design can perform two transcendental mathematical operations called logarithm and powering, and three commonly used computations with similar operations named polynomial calculation, filtering, and windowing. By analyzing the adopted algorithms of the above five operations, a simplified computing unit is designed. This unit can combine six types of operations by reconfiguring the data paths, and the same multiplyadd architecture can be reused for reducing the redundant usage of logic gates. The experimental results reveal that the proposed design can work at a 200-MHz clock rate, and its gate count only has 11.9k. Compared with the results of the floating-point function, the median errors of the proposed design for computing the powering and logarithmic functions are 0.57% and 0.11%, respectively. Such results indicate that this simple architecture can be effectively used in most speech processing applications.Index Terms-Fixed-point system, iterative design, speech processing.

This work presents a low-complexity algorithm for multi-level smile intensity measurement based on mouth-corner features (MCFs). The proposed MCFs-based algorithm uses the mouth region images and accumulates the value of enhanced grayscale pixels along the horizontal axis. To further analyze the mouth shape, the local maximum information of the accumulated values is extracted to identify the height and width sizes of an opening mouth. Finally, the normalized threshold method is adopted to measure the smile intensity. The experimental results have shown that the proposed approach can achieve an average accuracy rate of 80% for the smiling measuring with four different levels of intensity. Moreover, the proposed algorithm can measure the smile intensity in a multi-face environment. Such results have demonstrated the efficiency and the feasibility of proposed algorithm.

No abstract

No abstract