forensic phonetics

Previous studies have demonstrated the efficacy of speech rhythm measures in speaker identification across various languages with different phonotactic structures. In Persian language, in particular, two categories of speech rhythm metrics were examined: duration-based and intensity-based metrics. Building upon these prior works, the current study delves deeper into the discrimination capabilities of the mentioned measurement types—duration-based versus intensity-based—in the context of Persian speakers. To achieve this, a multinomial logistic regression model was employed on a dataset comprising 20 male Persian speakers, each reciting 100 sentences at a normal speaking pace. Findings revealed that, when distinguishing between Persian speakers, duration-based measures outperform intensity-based ones, however, this excellence is very slight. This observation is significant, as it sheds light on the suitability of specific rhythm metrics for Persian speaker identification. I postulate that this discrepancy in performance may be attributed to the simple syllable structure of Persian and the lesser reliance on intensity as a primary indicator of lexical stress. This research contributes valuable insights into the choice of rhythm metrics for optimal Persian speaker identification and underscores the importance of considering linguistic features when developing speaker recognition systems.Top of Form