Feature extraction is still a disputed issue for the recognition of emotions from speech. Differences in features for male and female speakers are a well-known problem and it is established that gender-dependent emotion recognizers perform better than gender-independent ones. We propose a way to improve the discriminative quality of gender-dependent features: The emotion recognition system is p...

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of so...

Philosophers engaged in projects of ‘ameliorative inquiry’ offer accounts social categories, such as those race and gender, that set aside the descriptive question understanding categories they currently exist favour developing how we ought to think given our political goals. For feminists whose goal is combat gender injustice, dictionary definition ‘woman’ ‘adult human female’ has, on face it,...

Human face/gait-based gender recognition has been intensively studied by the previous literatures, yet most of them are based on the same database. Although nearly perfect gender recognition rates can be achieved in the same face/gait dataset, they assume a closed-world and neglect the problems caused by dataset bias. Real-world human gender recognition system should be dataset-independent, i.e...

In an experiment, the authors investigated the impact of gender categorization on face recognition. Participants were familiarized with composite androgynous faces labeled with either a woman's first name (Mary) or a man's first name (John). The results indicated that participants more quickly eliminated faces of the opposite gender than faces of the same gender than the face they were looking ...

We would like to incorporate speaker-dependent consistencies, such as gender, in an otherwise speaker-independent speech recognition system. In this paper we discuss a Gender Dependent Neural Network (GDNN) which can be tuned for each gender, while sharing most of the speaker independent parameters. We use a classification network to help generate gender-dependent phonetic probabilities for a s...

In this paper, through different experimental studies it is demonstrated that the time varying glottal excitation component of speech can be exploited for text independent gender recognition studies. Linear prediction (LP) residual is used as a representation of excitation information in speech. The gender-specific information in the excitation of voiced speech is captured using the Hidden Mark...