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• Resumen es exacto "Some of the most popular applications of speaker recognition are: financial, forensic and legal, security, audio and video indexing, surveillance, teleconferencing, and e-learning. This work focuses on forensic applications, and seeks to improve automatic speaker recognition systems by incorporating distinctive long-term features to actual short-term information.
  We can summarize the overall objective of this thesis as the "incorporation of long-term information to an automatic speaker recognition system based on standard segmental parameters to be used in forensic applications."
  The proposed hypothesis suggests that if you manage to find segmental characteristics of higher order and suprasegmental features that are useful for people discrimination, the multiparametric system will perform better in the recognition task, since it will have more information about the speaker. The main sources for the determination of these features will neuroscience and linguistics, considering that valuable knowledge can be extracted from the analysis of the innate ability of humans to recognize people by their voice."

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