This paper investigates the most accent-sensitive words for Malaysian English (MalE) speakers in multi-resolution 13 Mel-frequency cepstral coefficients. A text-independent accent system was implemented using different numbers of Mel-filters to determine the optimal settings for this database. Then, text-dependent accent systems were developed to rank the most accent-sensitive words for MalE speakers according to the classification rates. Prior work has also been conducted to test the significance of the wordlist for both gender and accent factors, and to investigate any interaction between these two factors. Experimental results show that male speakers have a higher intensity of accent effects compared with female speakers by 3.91% on text-independent and 3.47% on text-dependent tasks. Another finding has proven that by selecting appropriate words that carry severe accent markers could improve the task of speaker accent classification. An improvement of at most 8.45% and 8.91% was achieved on the male and female datasets, respectively, following vocabulary selection.
