Titlebook: Cross-Word Modeling for Arabic Speech Recognition; Dia AbuZeina,Moustafa Elshafei Book 2012 Dia AbuZeina 2012 Arabic linguistics.Arabic ph

JADE

书目名称Cross-Word Modeling for Arabic Speech Recognition影响因子(影响力)




书目名称Cross-Word Modeling for Arabic Speech Recognition影响因子(影响力)学科排名




书目名称Cross-Word Modeling for Arabic Speech Recognition网络公开度




书目名称Cross-Word Modeling for Arabic Speech Recognition网络公开度学科排名




书目名称Cross-Word Modeling for Arabic Speech Recognition被引频次




书目名称Cross-Word Modeling for Arabic Speech Recognition被引频次学科排名




书目名称Cross-Word Modeling for Arabic Speech Recognition年度引用




书目名称Cross-Word Modeling for Arabic Speech Recognition年度引用学科排名




书目名称Cross-Word Modeling for Arabic Speech Recognition读者反馈




书目名称Cross-Word Modeling for Arabic Speech Recognition读者反馈学科排名

善于

言行自由

Reconstructing Teachers of MathematicsThis chapter presents a brief overview of the evolution of Arabic speech recognition systems. It provides a literature survey of Arabic speech recognition systems and discusses some of the challenges of Arabic from the speech recognition point of view.

Deadpan

BROW

Reconstructing Teachers of MathematicsThis chapter discusses some Arabic phonological rules that can be used to capture the variations occurring at words’ junctures. The rules include Idgham, Iqlaab, Hamzat Al-Wasl, and merging of two consecutive unvoweled letters. Then, an algorithm to model this problem is provided.

皱痕

Wetlands: A Multidisciplinary PerspectiveThis chapter presents the results achieved by modeling cross-word pronunciation variation problem of MSA. We practically investigated two MSA phonological rules (Idgham and Iqlaab) which significantly enhanced recognition accuracy. Three ASR’s metrics were measured: word error rate (WER), out of vocabulary (OOV), and perplexity (PP).

皱痕

Arabic Speech Recognition Systems,This chapter presents a brief overview of the evolution of Arabic speech recognition systems. It provides a literature survey of Arabic speech recognition systems and discusses some of the challenges of Arabic from the speech recognition point of view.

伪书

Cross-Word Pronunciation Variations,This chapter presents the cross-word problem of the Arabic language. It also includes the main sources of this problem: Idgham (merging), Iqlaab (changing), Hamzat Al-Wasl deleting, and merging of two consecutive unvoweled letters. Illustrative examples of the cross-word problem are also provided.

抵制

Modeling of Arabic Cross-Word Pronunciation Variations,This chapter discusses some Arabic phonological rules that can be used to capture the variations occurring at words’ junctures. The rules include Idgham, Iqlaab, Hamzat Al-Wasl, and merging of two consecutive unvoweled letters. Then, an algorithm to model this problem is provided.

ANIM

Performance and Evaluation,This chapter presents the results achieved by modeling cross-word pronunciation variation problem of MSA. We practically investigated two MSA phonological rules (Idgham and Iqlaab) which significantly enhanced recognition accuracy. Three ASR’s metrics were measured: word error rate (WER), out of vocabulary (OOV), and perplexity (PP).