State-of-the-art in speaker recognition

TL;DR

This paper reviews recent advancements in speaker recognition technology, highlighting its advantages over other biometric methods and discussing ongoing research directions like improved classification and probabilistic grammars.

Contribution

It provides a comprehensive overview of the current state of speaker recognition, emphasizing its flexibility, potential, and the areas where further research is needed.

Findings

Speaker recognition offers more flexibility than fingerprint or iris methods.

Current research focuses on improved classification systems.

Use of probabilistic grammars enhances recognition capabilities.

Abstract

Recent advances in speech technologies have produced new tools that can be used to improve the performance and flexibility of speaker recognition While there are few degrees of freedom or alternative methods when using fingerprint or iris identification techniques, speech offers much more flexibility and different levels for performing recognition: the system can force the user to speak in a particular manner, different for each attempt to enter. Also with voice input the system has other degrees of freedom, such as the use of knowledge/codes that only the user knows, or dialectical/semantical traits that are difficult to forge. This paper offers and overview of the state of the art in speaker recognition, with special emphasis on the pros and contras, and the current research lines. The current research lines include improved classification systems, and the use of high level information by means of probabilistic grammars. In conclusion, speaker recognition is far away from being a technology where all the possibilities have already been explored.