Algerian Arabic rhythm classification

Droua-Hamdani, Ghania; Selouani, Sid‐Ahmed; Boudraa, Malika; Cichocki, Wladyslaw

doi:10.36505/exling-2010/03/0010/000130

Cited by 2 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With reference to previous studies of Arabic rhythm (see 2.1), YA shows similar patterns with the western Arabic dialects due the high values obtained by both indexes applied in the study, and these values reflect the high stress-timing features of this dialect which are similar to those of the western dialects (e.g. Hamdi-Sultan et al, 2004, Ghazali et al, 2007and Droua-Hamdani, Selouani, Boudraa & Cichocki, 2010. Moreover, although the two groups spoke the same dialect, they displayed significant differences in their rhythmic output which indicates that rhythm in YA is undergoing change.…”

Section: Resultssupporting

confidence: 80%

An acoustic analysis of the rhythm of Yemeni Arabic

Salem¹,

Pillai²

2019

JML

View full text Add to dashboard Cite

Previous studies have found that different Arabic dialects display different degrees of stress-timing features forming a continuum that ranges from more stress-timed to less stress-timed Arabic dialects. This study investigated the vocalic durational intervals of speakers from two groups of speakers, Yemeni younger generation (YYG) and Yemeni older generation (YOG), both in reading and spontaneous speech by means of two indexes, namely, nPVI and Varco V. The results revealed that Yemeni speakers displayed stresstiming features in both the read passage and spontaneous speech contexts. However, whereas the rhythmic patterns in their read speech appeared to be comparable for both YYG and YOG speakers, significant differences were found in their spontaneous speech. This was in terms of the nPVI and VarcoV measurements where the rhythmic output of YYG speakers appeared to be more stress-timed than their older counterparts. The high values obtained by both indexes in the study show that YA patterns with prototypical stress-timed languages such as English, Dutch, Thai and the highly stress-timed western Arabic dialects.

show abstract

Section: Resultssupporting

confidence: 80%

An acoustic analysis of the rhythm of Yemeni Arabic

Salem¹,

Pillai²

2019

JML

View full text Add to dashboard Cite

show abstract

“…MSA, English, and French language on the (%V, ∆C) plane. The measures of Algerian MSA, English, and French prosodic features are taken from Droua et al [54].…”

Section: Cross-dialectal Comparison Shows That the Proportion Of Voca...mentioning

confidence: 99%

“…The second group represents the syllable-timed rhythm class, such as French, which include Sulaymite dialect. The third group includes Ma'qilian and Urban Completely Bedouin dialect that is near to Algerian-MSA language, which is classified to Mixedtimed rhythm class [54].…”

Section: Cross-dialectal Comparison Shows That the Proportion Of Voca...mentioning

confidence: 99%

Hierarchical Classification for Spoken Arabic Dialect Identification using Prosody: Case of Algerian Dialects

Bougrine,

Cherroun,

Ziadi

2017

Preprint

View full text Add to dashboard Cite

In daily communications, Arabs use local dialects which are hard to identify automatically using conventional classification methods. The dialect identification challenging task becomes more complicated when dealing with an under-resourced dialects belonging to a same county/region. In this paper, we start by analyzing statistically Algerian dialects in order to capture their specificities related to prosody information which are extracted at utterance level after a coarse-grained consonant/vowel segmentation. According to these analysis findings, we propose a Hierarchical classification approach for spoken Arabic algerian Dialect IDentification (HADID). It takes advantage from the fact that dialects have an inherent property of naturally structured into hierarchy. Within HADID, a top-down hierarchical classification is applied, in which we use Deep Neural Networks (DNNs) method to build a local classifier for every parent node into the hierarchy dialect structure. Our framework is implemented and evaluated on Algerian Arabic dialects corpus. Whereas, the hierarchy dialect structure is deduced from historic and linguistic knowledges. The results reveal that within HADID, the best classifier is DNNs compared to Support Vector Machine. In addition, compared with a baseline Flat classification system, our HADID gives an improvement of 63.5% in term of precision. Furthermore, overall results evidence the suitability of our prosody-based HADID for speaker independent dialect identification while requiring less than 6s test utterances.

show abstract

Algerian Arabic rhythm classification

Cited by 2 publications

References 3 publications

An acoustic analysis of the rhythm of Yemeni Arabic

An acoustic analysis of the rhythm of Yemeni Arabic

Hierarchical Classification for Spoken Arabic Dialect Identification using Prosody: Case of Algerian Dialects

Contact Info

Product

Resources

About