High quality Arabic text-to-speech synthesis using unit selection

Abdelmalek, Raja; Mnasri, Zied

doi:10.1109/ssd.2016.7473681

Cited by 8 publications

(4 citation statements)

References 6 publications

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“…Table XII lists the techniques used to evaluate the studies. The subjective evaluation method was commonly applied to evaluate TTS systems, and the most commonly used method was the Mean Opinion Score (MOS) test [88], [92], [93], [94], [99], [103], [104], [105], [61], [106], [108], [110], [112], [114], [115], [117], [118], [119]. Categorial estimation (CE) tests, preference test [102], [108], [117], DMOS test [108], and DRT tests [87], [96], [116] have also been used as subjective evaluation tests in some studies.…”

Section: ) Rq5: Evaluation Techniques and Resultsmentioning

confidence: 99%

“…Categorial estimation (CE) tests, preference test [102], [108], [117], DMOS test [108], and DRT tests [87], [96], [116] have also been used as subjective evaluation tests in some studies. Most studies measured intelligibility [91], [94], [95], [96], [99], [103], [104], [105], [61], [106], [109], [110], [112], [115], [116], [118], [120] and naturalness [94], [95], [99], [101], [103], [104], [105], [108], [109], [112], [115], [116], [118] whereas others measured pronunciation [95], [109], sound quality [95], [109], [111], prosody [91], nasality [87], graveness [87], compactness [87], clearness ...…”

Section: ) Rq5: Evaluation Techniques and Resultsmentioning

confidence: 99%

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Advancements in Arabic Text-to-Speech Systems: A 22-Year Literature Review

Chemnad

Othman

2023

IEEE Access

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Although there are several speech synthesis models available for different languages tailored to specific domain requirements and applications, there is currently no readily available information on the latest trends in Arabic language speech synthesis. This can make it challenging for beginners to research and develop text-to-speech (TTS) systems for Arabic languages. To address this issue, this article provides a comprehensive overview of several scholars' contributions to the field of Arabic TTS, along with an examination of the unique features of the Arabic language and the corresponding challenges in creating TTS systems. Reporting only on papers discussing Arabic TTS, this systematic review evaluated the available literature published between 2000 and 2022. We conducted a systematic review in six databases using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines to identify studies that addressed Arabic Text-to-Speech systems. Of a total of 3719 articles identified, only 36 (0.96%) articles met our search criteria. Bibliometric analyses of these studies were conducted and reported. The results highlight the main types of speech synthesis techniques used in TTS systems: concatenative, formant, deep neural network (DNN), hybrid models, and multiagent. The corpora used to develop these systems, as well as the diacritization techniques incorporated, evaluation techniques, and the results of the performance of the systems are reported. Subjective evaluation using the mean opinion score is most applied to measure the accuracy of systems. This study also identifies gaps in the literature and makes recommendations for future research directions.

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Section: ) Rq5: Evaluation Techniques and Resultsmentioning

confidence: 99%

Section: ) Rq5: Evaluation Techniques and Resultsmentioning

confidence: 99%

Advancements in Arabic Text-to-Speech Systems: A 22-Year Literature Review

Chemnad

Othman

2023

IEEE Access

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“…Application of TTS to the Arabic language has started since the beginning of TTS technology. Unit selection TTS was successfully adapted to Arabic [20] as well as the HMM-based TTS toolkit (HTS) [14]. Also in [14], the synthesis filter was modified to improve its quality: the set of acoustic parameters consisted of spectrum amplitude and multi-band voicing decision, and the MLSA filter has been replaced by a multi-band excitation vocoder [21].…”

Section: Arabic Parametric Ttsmentioning

confidence: 99%

Duration modelling and evaluation for Arabic statistical parametric speech synthesis

Zangar

Mnasri

Colotte

et al. 2020

Multimed Tools Appl

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Sound duration is responsible for rhythm and speech rate. Furthermore, in some languages phoneme length is an important phonetic and prosodic factor. For example, in Arabic, gemination and vowel quantity are two important characteristics of the language. Therefore, accurate duration modelling is crucial for Arabic TTS systems. This paper is interested in improving the modelling of phone duration for Arabic statistical parametric speech synthesis using DNN-based models. In fact, since a few years, DNN have been frequently used for parametric speech synthesis, instead of HMM. Therefore, several variants of DNN-based duration models for Arabic are investigated. The novelty consists in training a specific DNN model for each class of sounds, i.e. short vowels, long vowels, simple consonants and geminated consonants. The main idea behind this choice is the improvement that we already achieved in the quality of Arabic parametric speech synthesis by the introduction of two specific features of Arabic, i.e. gemination and vowel quantity into the standard HTS feature set. Both objective and subjective evaluations show that using a specific model for each class of sounds leads to a more accurate modelling of the phone duration in Arabic parametric speech synthesis, outperforming the state-of-the-art duration modelling systems.

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“…As far as Arabic speech is concerned, Arabic TTS systems have been developed since the beginning of TTS technology. Unit selection TTS was successfully adapted to Arabic [11] as well as HTS [12]. Recently, a new set of linguistic features, that takes care of Arabic phonemes specificities, such as vowel quantity and consonant gemination, has been successfully introduced into the HTS system, to better fit it to Arabic language [13].…”

Section: Introductionmentioning

confidence: 99%

Duration modeling using DNN for Arabic speech synthesis

Zangar¹,

Mnasri²,

Colotte³

et al. 2018

Speech Prosody 2018

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Duration modeling is a key task for every parametric speech synthesis system. Though such parametric systems have been adapted to many languages, no special attention was paid to explicitly handling Arabic speech characteristics. Actually, in Arabic phoneme duration has a distinctive role, because of consonant gemination and vowel quantity. Therefore, a precise modeling of sound durations is critical. In this paper we compare several modeling of phoneme durations (including duration modeling by HTS and MERLIN toolkits), and we propose a new approach which relies on using a set of models, each one being optimal for a given phoneme class (e.g., simple consonants, geminated consonants, short vowels, and long vowels). An objective evaluation carried out on a set of test sentences shows that the proposed approach leads to a more accurate modeling of the phoneme durations.

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High quality Arabic text-to-speech synthesis using unit selection

Cited by 8 publications

References 6 publications

Advancements in Arabic Text-to-Speech Systems: A 22-Year Literature Review

Advancements in Arabic Text-to-Speech Systems: A 22-Year Literature Review

Duration modelling and evaluation for Arabic statistical parametric speech synthesis

Duration modeling using DNN for Arabic speech synthesis

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