Wang Chao

The main goal of this study is to explore the drivers of meaningful sport consumption and its influence mechanism. In sports consumption, consumers not only seek hedonic value but also pursue to experience greater purpose and meaning in life, which is regarded as meaningful sports consumption. This study extends existing sports management literature by examining how social needs impact meaningful sports behavior with team affiliation, self-improvement, and self-esteem as mediators. Based on the questionnaire data collected from China, the empirical analysis results show that social needs have a significant positive impact on meaningful sports consumption behavior through the mediating effect of team affiliation and self-esteem motivation. However, self-improvement motivation does not have a mediating effect on the relationship between social needs and meaningful sports consumption. This study enriches the research content of sports consumption, adds research object of social needs, and expands the research scope of meaningful consumption by introducing meaningful sports consumption into the above domain.

In speaker recognition systems, feature extraction is a challenging task under environment noise conditions. To improve the robustness of the feature, we proposed a multiscale chaotic feature for speaker recognition. We use a multiresolution analysis technique to capture more finer information on different speakers in the frequency domain. Then, we extracted the speech chaotic characteristics based on the nonlinear dynamic model, which helps to improve the discrimination of features. Finally, we use a GMM-UBM model to develop a speaker recognition system. Our experimental results verified its good performance. Under clean speech and noise speech conditions, the ERR value of our method is reduced by 13.94% and 26.5% compared with the state-of-the-art method, respectively.