| dc.description.abstract |
In the ever-changing technological landscape, speech recognition stands out as a growing discipline within the field of natural language processing (NLP). This major breakthrough in human-machine interfaces has dramatically reshaped the way we interact with the digital systems and intelligent environments around us. Speech recognition, as a cornerstone of this revolution, aims to accurately and quickly translate the complex modulations of the human voice into text, thus opening up a multitude of applications ranging from virtual assistants and voice control systems to digital devices, communication aid and automated transcription. It will also facilitate illiterate people's access to various digital services and improve financial inclusion. This article dives deep into the state of the art in speech recognition, exploring technological advances, cutting-edge algorithmic models, deep learning methodologies, and persistent challenges driving research such as low-resource languages, multilingual models and innovation in this constantly evolving field. By taking a close look at the progress made, current gaps and future prospects, this review aims to offer a comprehensive overview of the most recent and relevant developments in speech recognition. |
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