Classification of Turkish Vowels Based on Formant Frequencies

Korkmaz, Yunus; Boyacı, Aytuğ

doi:10.1109/idap.2018.8620877

Cited by 9 publications

(3 citation statements)

References 4 publications

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“…/a/ presents a rapprochement of F1 and F2, F1 has a maximum value around 1000 Hz. Korkmaz and Aytug [10] exploited the formant frequency values (F1, F2 and F3) of eight Turkish vowels within CVC syllables to identify the most efficient classification method. They deduced that support vector machines (SVM) distinguishes Turkish vowels from formant frequencies with a classification success of 90%.…”

Section: Introductionmentioning

confidence: 99%

Efficiency of the energy contained in modulators in the Arabic vowels recognition

Abajaddi¹,

Elfahm²,

Mounir

et al. 2021

IJECE

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<span>The speech signal is described as many acoustic properties that may contribute differently to spoken word recognition. Vowel characterization is an important process of studying the acoustic characteristics or behaviors of speech within different contexts. This current study focuses on the modulators characteristics of three Arabic vowels, we proposed a new approach to characterize the three Arabic vowels /a/, /i/ and /u/. The proposed method is based on the energy contained in the speech modulators. The coherent subband demodulation method related to the spectral center of gravity (COG) was used to calculate the energy of the speech modulators. The obtained results showed that the modulators energy help characterize the Arabic vowels /a/, /i/ and /u/ with an interesting recognition rate ranging from 86% to 100%.</span>

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Section: Introductionmentioning

confidence: 99%

Efficiency of the energy contained in modulators in the Arabic vowels recognition

Abajaddi¹,

Elfahm²,

Mounir

et al. 2021

IJECE

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show abstract

“…In articulatory phonetics, /a/ being the least anterior and most open front vowel, has a rear cavity affiliated with a very high F1, exhibiting intermediate lowering and advancement of the tongue. Because the first two formants F1 and F2 are concentrated in the low frequencies (F1>100 Hz and F2 1,000 Hz), the energy of the vowel /u/, which is the most closed, posterior, and rounded, is concentrated in the first band B1 [32], [33].…”

Section: Discussionmentioning

confidence: 99%

Characterization of Arabic sibilant consonants

Elfahm¹,

Abajaddi²,

Mounir

et al. 2023

IJECE

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The aim of this study is to develop an automatic speech recognition system in order to classify sibilant Arabic consonants into two groups: alveolar consonants and post-alveolar consonants. The proposed method is based on the use of the energy distribution, in a consonant-vowel type syllable, as an acoustic cue. The application of this method on our own corpus reveals that the amount of energy included in a vocal signal is a very important parameter in the characterization of Arabic sibilant consonants. For consonants classifications, the accuracy achieved to identify consonants as alveolar or post-alveolar is 100%. For post-alveolar consonants, the rate is 96% and for alveolar consonants, the rate is over 94%. Our classification technique outperformed existing algorithms based on support vector machines and neural networks in terms of classification rate.

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“…Therefore, non-native speakers may be more sensitive to the phonological characteristics of syllables in grammatical and ungrammatical conditions. This may reflect the difference in formant frequencies in Farsi and Turkish vowels ( Modaresi Ghavami, 2011 ; Korkmaz and Boyaci, 2018 ) where frequencies of F1 and F2 for the Farsi vowels /a/ and /i/ are higher than in their Turkish counterparts. Since we are not aware of similar reports, this finding should be followed up in future studies.…”

Section: Discussionmentioning

confidence: 99%

First Event-Related Potentials Evidence of Auditory Morphosyntactic Processing in a Subject-Object-Verb Nominative-Accusative Language (Farsi)

et al. 2021

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While most studies on neural signals of online language processing have focused on a few—usually western—subject-verb-object (SVO) languages, corresponding knowledge on subject-object-verb (SOV) languages is scarce. Here we studied Farsi, a language with canonical SOV word order. Because we were interested in the consequences of second-language acquisition, we compared monolingual native Farsi speakers and equally proficient bilinguals who had learned Farsi only after entering primary school. We analyzed event-related potentials (ERPs) to correct and morphosyntactically incorrect sentence-final syllables in a sentence correctness judgment task. Incorrect syllables elicited a late posterior positivity at 500–700 ms after the final syllable, resembling the P600 component, as previously observed for syntactic violations at sentence-middle positions in SVO languages. There was no sign of a left anterior negativity (LAN) preceding the P600. Additionally, we provide evidence for a real-time discrimination of phonological categories associated with morphosyntactic manipulations (between 35 and 135 ms), manifesting the instantaneous neural response to unexpected perturbations. The L2 Farsi speakers were indistinguishable from L1 speakers in terms of performance and neural signals of syntactic violations, indicating that exposure to a second language at school entry may results in native-like performance and neural correlates. In nonnative (but not native) speakers verbal working memory capacity correlated with the late posterior positivity and performance accuracy. Hence, this first ERP study of morphosyntactic violations in a spoken SOV nominative-accusative language demonstrates ERP effects in response to morphosyntactic violations and the involvement of executive functions in non-native speakers in computations of subject-verb agreement.

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Classification of Turkish Vowels Based on Formant Frequencies

Cited by 9 publications

References 4 publications

Efficiency of the energy contained in modulators in the Arabic vowels recognition

Efficiency of the energy contained in modulators in the Arabic vowels recognition

Characterization of Arabic sibilant consonants

First Event-Related Potentials Evidence of Auditory Morphosyntactic Processing in a Subject-Object-Verb Nominative-Accusative Language (Farsi)

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