Today, speech recognition is considered as one of the disruptive technologies that makes huge impact in banking, insurance, retail and manufacturing industries. The global market value of speech analytics is estimated to grow USD $456 million in 2014 to 1.33 billion by the year 2019 according to reports from Markets.
Speech recognition solutions enables natural, human-like conversations with machines and can achieve very high accuracy levels with appropriate fine tuning around vernacular attributes. By its enormous growth and rising popularity, it is becoming increasingly mainstream among different industries and enterprises. In India, where 70% of the country’s population is involved in the agriculture industry, speech technology has started been playing a critical role through user friendly speech solutions to rural farmers.
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Signals are ubiquitous across many research and development domains. Engineers and scientists need to process, analyze, and extract information from time-domain data as part of their day-to-day responsibilities. In a range of predictive analytics applications, signals are the raw data that machine learning systems must be able to leverage for the purpose of creating understanding and for informing decision-making.
For a company like Google or Amazon, hundreds and thousands hours of spoken audio are recorded in real-life situations. That’s the single biggest thing which separates their world-class speech recognition system from your hobby system.
Main features of Signal Processing are:
Every single thing you say into one of these systems is recorded forever and used as training data for future versions of speech recognition algorithms.