Abstract
Abstract
In recent few years, deep learning has fast growing in many fields as natural language processing, image recognition, handwriting recognition, computer vision, and speech recognition. Automatic speech recognition (ASR) is a technique that refers to translating spoken words from an acoustic waveform into a text equivalent to what the speaker says. More recently, the advances in deep learning can support ASR in improving the performance of systems accuracies. Arabic is a Semitic language, one of the oldest used and most communicated languages in the world. But, it least concentrated in the case of Arabic speech recognition and under-resourced languages. This paper presents a survey that focuses on an automatic speech recognition system based on isolating words technique for Arabic speech. It also highlights the facilities and tools for developing speech recognition systems. This work is intended to be a useful starting point for those who are interested in ASR.
Subject
General Physics and Astronomy
Reference39 articles.
1. Speech recognition based on convolution neural network;Du,2016
2. Arabic speech recognition using recurrent neural networks;El Choubassi,2004
3. Review on Speech Recognition using Deep Learning;Dayal;International Journal for Research in Applied Science & Engineering Technology (IJRASET),2020
4. Align tool: the automatic temporal alignment of spoken utterances in german, dutch, and british english for psycholinguistic purposes;Schillingmann,2018
5. Automated speech analysis tools for children’s speech production: A systematic literature review;McKechnie,2018
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献