Deep learning techniques such as convolutional neural networks (CNN) have been
successfully applied to identify pathological voices. However, the major disadvantage of …

During phonation, the vocal folds exhibit a self-sustained oscillatory motion, which is
influenced by the physical properties of the speaker's vocal folds and driven by the balance …

In this paper, we present a study on the efficiency of neural networks for the hard problem of
automatically classifying voice disorders. To this end, convolutional architectures combined …

Goal: Numerous studies had successfully differentiated normal and abnormal voice
samples. Nevertheless, further classification had rarely been attempted. This study proposes …

Machine learning has the potential to help optimize, assess, predict, and rehabilitate voice
and swallowing function in head and neck cancer patients as well as aid in cancer …

In this work we perform a scoping review of the current literature on the detection of throat
cancer from speech recordings using machine learning and artificial intelligence. We find 22 …

So far, several physical models have been proposed for the study of vocal fold oscillations
during phonation. The parameters of these models, such as vocal fold elasticity, resistance …

The development of methods that combine different sources of information for medical
diagnosis is an essential challenge in the field of medical informatics. In this context, we …

A property vector representing extractable measurable properties, such as musical
properties, of a file is mapped to semantic properties for the file. This is achieved by using …

The invention provides for the evaluation of semantic close ness of a source data file relative
to candidate data files. The system includes an artificial neural network and processing …