Speech analytics is the process of analyzing recorded calls to gather customer information to improve communication and future interaction.
The process is primarily used by customer contact centers to extract information buried in client interactions with an enterprise.
The technology can pinpoint cost drivers, trend analysis, identify strengths and weaknesses with processes and products, and help understand how the marketplace perceives offerings.
This information is useful for supervisors, analysts, and others in an organization to spot changes in consumer behavior and take action to reduce call volumes—and increase customer satisfaction.
[8] Measures such as Precision and recall, commonly used in the field of Information retrieval, are typical ways of quantifying the response of a speech analytics search system.
Where a standardised test set has been used, measures such as precision and recall can be used to directly compare the search performance of different speech analytics systems.
[12] Extended speech emotion recognition and prediction is based on three main classifiers: kNN, C4.5 and SVM RBF Kernel.
[14] The growth rate is attributed to rising requirements for compliance and risk management as well as an increase in industry competition through market intelligence.