Maral Asiaee; Mandana Nourbakhsh
Using the auditory-acoustic approach, the present study examines the possibility of using durational acoustic parameters of speech rhythm for detecting the Persian speakers’ use ...
Using the auditory-acoustic approach, the present study examines the possibility of using durational acoustic parameters of speech rhythm for detecting the Persian speakers’ use of Azeri as a form of voice disguise. To do so, continuous speech of 5 speakers of Standard Persian and 5 speakers of Azeri, Tabrizi variety, were chosen for the acoustic and statistical analysis after completing the validity procedures. All Persian speakers were monolingual and all Azeri speakers were bilingual speakers of Azeri and Persian, who spoke Azeri as their mother tongue and Persian as their second language. Each Persian speaker was asked to narrate a lifetime experience once in Persian (Persian- Persian data), and once as an imitation of Azeri (Persian- Azeri data). Azeri speakers were also asked to narrate a lifetime experience once in Azeri (Azeri- Azeri data) and once in Persian (Azeri-Persian Data). Persian-Azeri data is the type that is considered as the disguised data in this survey. The recorded data were then annotated in five tiers: segment, CV-segment, CV-segment interval, CV-interval and syllable. In order to control the effect of any unwanted variable, one minute (±5 seconds SD) of each sound file was extracted for further acoustic and statistical analyses. A Praat script, DurationAnalyzer, was used to automatically calculate the acoustic correlates of durational parameters of speech rhythm. These parameters are: %V (the proportion which speech is vocalic), ΔC (ln) (standard deviation of the natural-log normalized duration of consonantal intervals), ΔV (ln) (standard deviation of the natural-log normalized duration of vocalic intervals), nPVI- V (rate-normalized averaged durational differences between consecutive vocalic intervals) and syllable rate. Results revealed there was a significant difference between the proposed types of data and that%V and syllable rate best discriminated between them; however, none of the above-mentioned parameters were significantly different between Persian-Azeri and Azeri-Persian data.