Since they are not spoken in many areas, there are less publically available resources to work with them. Low resources languages are those languages that are not spoken in many parts of the world. Most state-of-the-art speech recognition software and tools work well on high resource languages such as English and Mandarin but perform very poorly on low resource languages such as Urdu and Persian etc. But even with all the resources allocated to it, speech recognition still has a lot to overcome. After the introduction of personal assistant tools, such as Alexa of Amazon, Google Assistant, Cortana of Microsoft and Siri of Apple, a lot of research resources have been allocated towards this field. But to make a machine that can perform this same task is proving to be quite a challenge. We humans automatically convert sound waves to text in our minds. Speech recognition is one of the few human skills that we need to make a machine truly human. An automated speech recognition system will be developed by applying multiple deep techniques to the gathered data. In this research, we will create a dataset with the help of a web and Android application.
The Urdu speech recognition can also be used as a base for training speech recognition system of many regional languages as well.
This shows the necessity to have an automated system that can recognize the Urdu language. Such tools fail to recognize the Urdu language. But most tools that are developed either use English or support languages that share roots with the English language. Pakistan being the sixth most populous country holds a huge market for voice-driven personal assistant tools. The English language may share roots with many European languages but fails when it comes to languages frequently spoken in the subcontinent. The major flaw with the presented system was that the high resource language used was also English. An assumption was made that the high resource and low resource language will share roots. One idea of dealing with low resource language is to use a high resource language in combination with the required low resource language. The major drawback of these tools is that they only recognize the English language speech or other high resource languages. Many efficient speech recognition tools exist in the market, and some are also available online. With the increase of such tools, the need for efficient speech recognition systems also increases. Voice-Driven personal assistant tools are increasing in the market. A lot of research has been done on this topic many voice-driven applications are proof of it. Speech recognition is one of the tools that will be needed to make a machine truly intelligent.
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