Language Research

The Persian Light Verbs’ Productivity

Mahdie Eshaghi; Gholamhosain Karimi doustan

Volume 12, Issue 2 , December 2022, , Pages 1-28

https://doi.org/10.22059/jolr.2021.315912.666682

Abstract

Rhythmic characteristics of speech based on consonantal and vocalic intervals as well as syllabic intervals vary between speakers of the same language. Nonetheless, the rhythmicity ... Read More Rhythmic characteristics of speech based on consonantal and vocalic intervals as well as syllabic intervals vary between speakers of the same language. Nonetheless, the rhythmicity of a speech signal is not solely dependent on the durational variability of phonetic intervals but it is also associated with the variability of the intensity patterns as well. Acoustic parameter of intensity is largely determined by the articulatory behaviors of the speech organs such as lip movement or mouth aperture. Therefore, it is plausible that speaker idiosyncrasy in movement of speech articulators and anatomical differences in individual’s vocal tracts may influence the energy distribution across a speech signal which subsequently leads to the variability in the values of the intensity measures. Using experimental phonetics tools and from an explicitly speaker-specific perspective, the present research attempts to explore potential speaker-specific acoustic parameters of speech rhythm which are extracted from the intensity contours across Persian speakers. This research aims to discover whether intensity-based measures of speech rhythm are able to discriminate between speakers in Persian. Two types of acoustic rhythmic measures based on the mean syllable intensity (stdevM, varcoM, rPVIm, nPVIm) and peak syllable intensity (stdevP, varcoP, rPVIp, nPVIp)) were selected for this study. Speech data from 12 Persian male speakers were recorded non-contemporaneously in laboratory environment on two different occasions separated by one to two weeks. Speech tokens were acoustically measured with PRAAT version 5.2.34 and statistical analyses were carried out with SPSS version 21 and R version 3.3.3. Results of the study indicated that speech rhythm measures based on intensity fluctuations play an important role in between-speaker rhythmic variability. In addition, discriminatory power of intensity-based measures is not affected by the language-dependent characteristics of Persian. The results also showed that the peak syllable intensity measures carry more speaker-specific information compared to the mean syllable intensity measures

Speech Rhythm Measures: Acoustic Cues for Speaker Identification

Homa Asadi; Batool alinezhad

Volume 12, Issue 2 , December 2022, , Pages 29-49

https://doi.org/10.22059/jolr.2021.304539.666624

Abstract

Durational Parameters of Speech Rhythm, A Measure for Detection of the Persian Speakers’ Use of Disguise?

Maral Asiaee; Mandana Nourbakhsh

Volume 11, Issue 1 , October 2020, , Pages 1-23

https://doi.org/10.22059/jolr.2020.298600.666587

Abstract

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 ... Read More 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.

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Keywords = Speech Rhythm

The Persian Light Verbs’ Productivity

Abstract

Speech Rhythm Measures: Acoustic Cues for Speaker Identification

Abstract

Durational Parameters of Speech Rhythm, A Measure for Detection of the Persian Speakers’ Use of Disguise?

Abstract