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For the past few years, artificial neural networks (ANNs) have been one of the most common solutions relied upon while developing automated speech recognition (ASR) acoustic models. There are several variants of ANNs, such as deep neural networks (DNNs), recurrent neural networks (RNNs), and convolutional neural networks (CNNs). A CNN model is widely used as a method for improving image processing...
This paper describes our work on automatic speech recognition system (ASR) for an under-resourced language, namely the Iban language, which is spoken in Sarawak, a Malaysian Borneo state. To begin this study, we collected 8 hours of speech data due to no resources yet for ASR concerning this language. Following the lack of resources, we employed bootstrapping techniques on a closely-related language...
This paper explores speech recognition performance for Malay language with multi accents from speakers of different origins or ethnicities. Accented speech imposes accuracy problem in automatic speech recognition systems. This frequently occurs to non-native speakers of a language due to insufficiency of the non-natives data in the recognizers. In this study, we investigate the mentioned problem by...
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