Automated grapheme-to-phoneme conversion for Central Kurdish based on optimality theory

Mahmudi, Aso; Veisi, Hadi

doi:10.1016/j.csl.2021.101222

Cited by 6 publications

(8 citation statements)

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“…There are 37 phonemes in SCK, including 8 vowels and 29 consonants [ 5 ]. This study uses the Hawar alphabet (standard Latin script for Northern Kurdish) with changes in some consonants.…”

Section: Background and Related Workmentioning

confidence: 99%

“…The long vowels (/î , ê , a , o , û/ ) are shorter in final unstressed positions, and the short vowel /e/ in word-final positions can be pronounced longer [ 6 ]. The vowel /i/ (bizroke) is unstable in most environments [ 7 ] and does not have a grapheme in the standard Kurdish alphabet [ 5 , 8 ].…”

Section: Background and Related Workmentioning

confidence: 99%

“…The Kurdish alphabet, which is adapted from the Perso-Arabic script, has ambiguities in three cases [ 5 ]:…”

Section: Background and Related Workmentioning

confidence: 99%

“…The proposed method utilizes a rule-based method of SCK grapheme-to-phonemes converter [ 5 ], which syllabifies the input poem. Then, for the analysis and detection of the poem meter, we consider all possible patterns of each line.…”

Section: Introductionmentioning

confidence: 99%

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Automatic meter classification of Kurdish poems

Mahmudi

Veisi

2023

PLoS ONE

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Most of the classic texts in Kurdish literature are poems. Knowing the meter of the poems is helpful for correct reading, a better understanding of the meaning, and avoiding ambiguity. This paper presents a rule-based method for the automatic classification of the poem meter for the Central Kurdish language also known as Sorani. The metrical system of Kurdish poetry is divided into three classes quantitative, syllabic, and free verses. As the vowel length is not phonemic in the language, there are uncertainties in syllable weight and meter identification. The proposed method generates all the possible situations and then, by considering all lines of the input poem and the common meter patterns of Kurdish poetry, identifies the most probable meter type and pattern of the input poem. Evaluation of the method on a dataset from VejinBooks Kurdish corpus resulted in 97.3% of precision in meter type and 96.2% of precision in pattern identification.

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“…There are 37 phonemes in SCK, including 8 vowels and 29 consonants [ 5 ]. This study uses the Hawar alphabet (standard Latin script for Northern Kurdish) with changes in some consonants.…”

Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

“…The Kurdish alphabet, which is adapted from the Perso-Arabic script, has ambiguities in three cases [ 5 ]:…”

Section: Background and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automatic meter classification of Kurdish poems

Mahmudi

Veisi

2023

PLoS ONE

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“…The normalization is much more important when it comes to the Kurdish Language since Kurdish writers and publishers utilize a variety of encoding schemes and orthographic standards [47] . To develop a text-to-speech system, we do text normalization, and the details of normalization completed on the text corpus are presented in [48,49] in our preprocessing stage. Some Kurdish writing includes a variety of numerical forms, such as date, time, and amounts.…”

Section: Pre-processingmentioning

confidence: 99%

End-to-End Kurdish Speech Synthesis Based on Transfer Learning

muhamad

Veisi

2022

PJBAS

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A text-to-speech (TTS) system converts the texts into speech in a specific language. Several TTS systems generate natural-like speech signals in numerous languages, such as English. On the other hand, the Kurdish language has just been examined. Existing preliminary research on Kurdish speech synthesis has utilized old methods and has generated low-quality speech. They also lack important aspects of speech, including intonation, emphasis, and rhythm. Some approaches were presented to address these challenges, including the use of concatenative systems. For example, the unit selection or statistical parametric methods. On the other hand, they need a great deal of time, effort, and domain knowledge. An additional factor for Kurdish speech synthesizers' low performance is the absence of publicly available speech corpora, unlike English, which has many freely-available corpora and audiobooks. The motivation of this paper is to create a Central Kurdish speech corpus and generate a human-like speech from the Kurdish text. This paper explains how to utilize Tacotron 2, an end-to-end neural network architecture and HiFi-GAN vocoder, to produce a high-quality, realistic, and human-like Kurdish voice. This work utilizes "text, audio" pairings, which contain 10 hours of recorded audio samples and texts collected from the Internet and textbooks. It shows how to use English character embedding as the pre-trained knowledge with Kurdish characters as input and how to preprocess these audio examples to get a great outcome. Our evaluations for various types of texts show a mean opinion score of 4.1, comparable with state-of-the-art synthesizers in other languages.

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