RESUMO
Unlike aspiration in stops, occurrence of aspiration in non-stop consonants is quite rare. Most of the languages that have aspirated non-stop consonants are low-resource languages. Hence, data driven, quantitative, and statistical analysis of their aspiration phenomena is fairly limited. Rabha and Angami are considered in this study, as previous studies have confirmed the existence of aspiration contrast in fricatives and nasals. This study reports the acoustic characteristics of aspiration in stops, fricatives, and nasals. Among them, distinguishing the aspirated fricatives and aspirated nasals from their unaspirated counterparts is a challenging task. A set of acoustic features is proposed to automatically detect the presence of aspiration in fricatives and nasals. Acoustic features, such as vocal tract constriction (VTC), normalized autocorrelation peak strength (NAPS), strength of excitation (SoE), and variance of successive epoch intervals (VSEI) are used to detect aspiration in fricatives and nasals. These features are extracted from zero-frequency filtered signal of the speech sounds, as it preserves the aspiration information. Results show that VTC, NAPS, and SoE can detect aspiration in nasals, whereas SoE and VSEI can detect aspiration in fricatives. The proposed method improves the performance of an automatic phoneme recognizer by reducing the confusion between aspirated and unaspirated counterparts.