Speech analytics

Speech Analytics is a term used to describe automatic methods of analyzing speech to extract useful information about the speech content or the speakers. Although it often includes elements of automatic speech recognition, where the identities of spoken words or phrases are determined, it may also include analysis of one or more of the following:
the topic(s) being discussed
the identities of the speaker(s)
the genders of the speakers
the emotional character of the speech

the amount and locations of speech versus non-speech (e.g. background noise or silence)
One use of speech analytics applications is to spot spoken keywords or phrases, either as real-time alerts on live audio or as a post-processing step on recorded speech. This technique is also known as audio mining. Other uses include categorization of speech, for example in the contact center environment, to identify calls from unsatisfied customers. Speech analytics technology may combine results from different techniques to achieve its aims. For example knowledge about where certain keywords were spoken in a customer telephone conversation could be combined with knowledge about which speaker (customer or contact center agent) spoke the words and perhaps knowledge of how often the two speakers were talking at the same time as each other.

Speech Analytics in contact centers can be used to extract critical business intelligence that would otherwise be lost. By analyzing and categorizing recorded phone conversations between companies and their customers, useful information can be discovered relating to strategy, product, process, and operational issues. This information gives decision-makers insight into what customers really think about their company so that they can quickly react.