Global automatic speech recognition market is expected to observe a high growth on account of increase in advanced electronic devices usage in the future. One of the major driver observed in the market is the increasing voice passwords use by consumers. Text passwords are difficult to remember and easy to crack.
Moreover, text passwords offer security threats. Therefore, organizations are focusing on adopting biometric passwords in the form of voice, which are easy to remember as well as operate by population. Over the past decades, the field of automatic speech recognition was mostly a research topic.
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With increase in the amount of fraud, organizations realized a need for a robust system which could serve the purpose for fraud management. In this system, a person’s voice is treated as a password for identification and authentication. The main objective of using automatic speech recognition application is to fasten the security system with high accuracy.
Such an application eradicates the need of a keyboard. Moreover, these applications have contributed to increase in accuracy, response time and efficiency which in turn is expected to drive its demand over the forecast period. Security systems based on voice are efficient in crowd control.
The need for entering correct passwords with keyboard for access results in time delays and long queues. Therefore, automatic voice based security systems are expected to find major applications where crowd control is required.
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Lack of supporting I.T infrastructure is hampering overall system growth as establishment of automatic speech recognition systems requires highly efficient I.T systems and maintenance. Mindset change is another factor which is expected to restrain global industry growth in the future.
Some organizations are expected to hesitate in implementing new technologies and stick with their old systems. Voice recognition consists of front end and back end techniques. Front end techniques do face a challenge of accuracy and time delay. Therefore, back end recognition technique is vastly used owing to its high precision and speed benefits.
These applications require a high amount of accuracy and should be able to handle disturbances or errors generated by noise. These systems also require high voice sensitivity detecting low pitch sounds as well.
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