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A Comparative Study of Different Speech Features for Arabic Phonemes Classification
TLDR
This paper presents the work related to phonetical analysis of classical Arabic speech. Expand
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Evaluation of an Arabic Speech Corpus of Emotions: A Perceptual and Statistical Analysis
TLDR
The processing of emotion has a wide range of applications in many different fields and has become the subject of increasing interest and attention for many speech and language researchers. Expand
  • 13
  • 1
Review of distinctive phonetic features and the Arabic share in related modern research
TLDR
This work reviews the research dealing with DPF strategies for digital speech and language processing using computing and engineering techniques and theories. Expand
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  • PDF
Diacritization, automatic segmentation and labeling for Levantine Arabic speech
TLDR
We propose methods to improve the BBN/AUB DARPA Babylon Levantine Arabic speech corpus to increase its reliability and efficiency. Expand
  • 6
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Distinctive Phonetic Features Modeling and Extraction Using Deep Neural Networks
TLDR
In this paper, the problem of DPF modeling and extraction of modern standard Arabic is tackled. Expand
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Preliminary Arabic speech emotion classification
TLDR
In this paper, the acoustic features of pitch, intensity, formants, and speech rate are extracted and used to classify the following Arabic speech emotions: neutral, sad, happy, surprised, and angry. Expand
  • 7
Investigating speaker gender using rhythm metrics in Arabic dialects
This paper investigates the relationship between speakers' gender and rhythm metrics (i.e., %V, ΔC, and ΔV) for three Arabic dialects, namely Modern Standard Arabic, Saudi Arabic, and Levantine. ToExpand
  • 5
Comparative evaluation of two arabic speech corpora
  • Y. Alotaibi, A. Meftah
  • Computer Science
  • Proceedings of the 6th International Conference…
  • 30 September 2010
TLDR
The aim of this paper is to conduct a constructive and comparative evaluation between two important Arabic corpora for two different Arabic dialects, namely, Saudi dialect corpus that was collected by King Abdulaziz City for Science and Technology (KACST), and a Levantine Arabic dialect corpus. Expand
  • 9
Emotional speech recognition: A multilingual perspective
This paper presents a comparison and analysis of speech emotion recognition in the context of Arabic and English languages. Four emotions (neutral, sadness, happiness and anger) were considered fromExpand
  • 4
Speaker Identification in Different Emotional States in Arabic and English
TLDR
We propose a speaker recognition system corresponding to three states, namely emotional, neutral, and with no consideration for a speaker’s state (i.e., the speaker can be in an emotional state or neutral state), for two languages: Arabic and English. Expand
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