A Neural Network Based Arabic Speech Filing System. | ||||
| MEJ- Mansoura Engineering Journal | ||||
| Article 3, Volume 18, Issue 1, March 1993, Page 72-80 PDF (348.99 K) | ||||
| Document Type: Research Studies | ||||
| DOI: 10.21608/bfemu.2021.164895 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Ahmed El-Saeed Tolba  1; Ibrahim Ibrahim Ismail2
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| 1Assistant Professor., Electrical Engineering Department ., University of Suez-Canal., Port-Said., Egypt. | ||||
| 2Electronics and Communications Department., University of Helwan., Cairo., Egypt. | ||||
| Abstract | ||||
| A natural man - machine communication with word processors requires the integration of speech recognition techniques. Speech recognition task is a difficult problem because of its temporal nature and the possibility of the presence of noise. Therefore, it is difficult to extract significant features by using the traditional techniques. Artificial neural networks introduce simple and fast learning techniques for this problem. This paper introduces the application of a three layer neural network for converting spoken Arabic words into Arabic text. We describe a supervised learning method which is based on the well known back propagation technique. The designed network proves itself to be speaker independent and noise immune word spotting guarantees invariance under translation in time. A user friendly word processor should nave intelligent interfaces such as the speaker interface and the hand writing interface. In this work we introduce the first interface. It is expected that neural network based speech-to-text transcription systems should have a significant effect on office | ||||
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