Nur-Hana Samsudin^1,*, Mark Lee²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1025-1039, 2022, DOI:10.32604/iasc.2022.022180

Abstract In a polyglot speech synthesis, it is possible to use one language resource for another language. However, if the adaptation is not implemented carefully, the foreignness of the sound will be too noticeable for the listeners. This paper presents the analysis of respondents’ acceptance of a series of listening tests. The research goal was to find out in the absence of phonemes of a particular language, would it be possible for the phonemes to be replaced with another language’s phonemes. This will be especially beneficial for under-resourced language either in the case for 1) the language has not yet well… More >

Mohamed Hashim Changrampadi^1,*, A. Shahina², M. Badri Narayanan², A. Nayeemulla Khan³

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1309-1323, 2022, DOI:10.32604/iasc.2022.022021

Abstract Research in speech recognition is progressing with numerous state-of-the-art results in recent times. However, relatively fewer research is being carried out in Automatic Speech Recognition (ASR) for languages with low resources. We present a method to develop speech recognition model with minimal resources using Mozilla DeepSpeech architecture. We have utilized freely available online computational resources for training, enabling similar approaches to be carried out for research in a low-resourced languages in a financially constrained environments. We also present novel ways to build an efficient language model from publicly available web resources to improve accuracy in ASR. The proposed ASR model… More >