… speaker embed- dings from a deep neural network (DNN) for text-independent speaker
verification. … and comparing i-vectors. We continue to use this two-stage approach in this work. …

… as well, including traditional methods and recent methods based on deep learning. Finally,
the … The above comparison examples all use the same video duration and sampling interval. …

… analysis (Lee et al., 2013) and hybrid methods (Lee et al., 2014). In response to the limited
availability of CFL learner data for machine learning and linguistic analysis, … , comparing with …

… translation involves transference between two different languages, … , its study can be
approached in different ways, such as by … equivalence between the source and the translated text …

… In recent years, AGI related technologies have made great progress in text processing,
machine … Adopting artificial intelligence and machine learning technologies to optimize risk …

… the context is political, I will include them in the analysis (see below). The reason for this
choice is that I consider the analyzed text to be a coherent thematic body and it would indeed be …

… was little difference between its prescriptions and those laid down five years earlier.Propaganda
and ideological work – and, externally, the projection of “soft power” – remained core …

… traditional machine learning (objective+regularization);2014 Since then , The rise of deep
learning … and materials of artificial intelligence ( Image & Text + video ) Introduction to machine …

… The main difference is whether the input data is labeled. The … Deep learning, also known as
a deep neural network, … the concept and classification of machine learning. We discussed the …

… This paper gives a comparative study on different techniques … Deep Neural Networks on
the other hand do not require any … concepts of artificial intelligence, machine learning, pattern …