Manuel Ortega-Rodríguez

Manuel Ortega-Rodríguez, Hugo Solís-Sánchez, Ricardo Gamboa-Alfaro

Exploiting the fact that natural languages are complex systems, the present exploratory article proposes a direct method based on frequency distributions that may be useful when making a decision on the status of problematic phonemes, an open problem in linguistics. The main notion is that natural languages, which can be considered from a complex outlook as information processing machines, and which somehow manage to set appropriate levels of redundancy, already "made the choice" whether a linguistic unit is a phoneme or not, and this would be reflected in a greater smoothness in a frequency versus rank graph. For the particular case we chose to study, we conclude that it is reasonable to consider the Spanish semiconsonant /w/ as a separate phoneme from its vowel counterpart /u/, on the one hand, and possibly also the semiconsonant /j/ as a separate phoneme from its vowel counterpart /i/, on the other. As language has been so central a topic in the study of complexity, this discussion grants us, in addition, an opportunity to gain insight into emerging properties in the broader complex systems debate.

Diana Valverde-Méndez, Manuel Ortega-Rodríguez, Hugo Solís-Sánchez et al.

Forensic speaker identification has traditionally considered approaches based on long term spectra analysis as especially robust, given that they work well for short recordings, are not sensitive to changes in the intensity of the sample, and continue to function in the presence of noise and limited passband. We find, however, that anger induces a significant distortion of the acoustic signal for long term spectra analysis purposes. Even moderate anger offsets speaker identification results by 33% in the direction of a different speaker altogether. Thus, caution should be exercised when applying this tool.