Investigating the use of multiple languages for crisp and fuzzy speaker identification

Abstract

The use of speech for system identification is an important and relevant topic. There are several ways of doing it, but most are dependent on the language the user speaks. However, if the idea is to create an all-inclusive and reliable system that uses speech as its input, we must take into account that people can and will speak different languages and have different accents. Thus, this research evaluates speaker identification systems on a multilingual setup. Our experiments are performed using three widely spoken languages which are Portuguese, English, and Chinese. Initial tests indicated the systems have certain robustness on multiple languages. Results with more languages decreases our accuracy, but our investigation suggests these impacts are related to the number of classes.