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Gender inequality is a widespread problem in our society. It can manifest itself in many ways and contexts, and starting as early as primary school. While an increasing number of initiatives aim at tackling gender biases and inequalities, few of them are a ...
In this paper, we analyze applicability of F0 and cepstral features, namely LPCCs, MFCCs, PLPs for robust Automatic Gender Recognition (AGR). Through gender recognition studies on BANCA corpus comprising datasets of varying complexity, we show that use of ...
When spreading information over social networks, seeding algorithms selecting users to start the dissemination play a crucial role. The majority of existing seeding algorithms focus solely on maximizing the total number of reached nodes, overlooking the is ...
Automatic Gender Recognition (AGR) is the task of identifying the gender of a speaker given a speech signal. Standard approaches extract features like fundamental frequency and cepstral features from the speech signal and train a binary classifier. Inspire ...
The challenge of knowing one's position in a precise and reliable way, at any time, with and without reception of satellite signals, represents an area fairly explored for the navigation of vehicles. To widen this service to the pedestrians requires a diff ...
Interpersonal skills require mastering a wide range of competencies such as communication and adaptation to different situations. Effective training includes the use of videos in which role models perform the desired behaviours such that trainees can learn ...
Deep learning-based algorithms have become increasingly efficient in recognition and detection tasks, especially when they are trained on large-scale datasets. Such recent success has led to a speculation that deep learning methods are comparable to or eve ...
Recent research has demonstrated the effectiveness of vocal tract length normalization (VTLN) as a rapid adaptation technique for statistical parametric speech synthesis. VTLN produces speech with naturalness preferable to that of MLLR-based adaptation tec ...
