WxCC Integration-3

Call Center Voice Analytics

What is a Call Center Voice Analytics?


Contact center voice analytics is a process that uses sophisticated computer tools to process audio recordings, convert speech into text, and extract insights from voice data. It is based on Natural Language Processing (NLP), and it analyzes speech patterns, emotional tone, and more from conversers to better understand how call centers can improve their services.

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How does call center voice analytics work?

Voice analytics solutions for contact and call centers focus on detecting certain aspects of conversation during a call and making notes or recording data about them. There are two principal ways in which computer technology achieves this.



One approach voice analytics software can take is to convert your words into phonemes, which are small, perceptually distinct units of sounds in speech (like p, b, t, oo in “food,” and ea in “easy”). There are 44 of them in the English language. The software analyzes these phonemes to recognize words and detect emotion and stress (emphasis) in the speakers’ voices. Doing so requires very sophisticated technology, as there is a lot of variation within languages, and even from the same speaker. Homophones (words that are pronounced the same but mean different things) can be difficult to process and require an understanding of the context around the word. And the same word pronounced in different accents can be recognized as using different phonemes. Difficulties can arise with speech-to-text software, sometimes even making the output unreadable.



A newer approach in contact center voice analytics is Large Vocabulary Conversational Speech Recognition (LVCSR), a technology that matches whole words instead of just phonemes. Doing so requires a huge database compared to what is required for phonetic analysis. This is because LVCSR uses different entries for the various ways each word is pronounced (e.g., “car” is said quite differently in Maryland, New York, and Boston). Thus data processing is slower, but the result is much more accurate.


Where phonetics look at the individual sounds that make up the words and puts them together into words (but can have trouble if it doesn’t recognize the sound strings), LVCSR looks for direct word matches, and strings them together into a sentence by processing a select number of words at a time. If all of the words fit together, LVCSR will produce a complete sentence that can be analyzed for emotional tone, etc.


What can call center voice analytics tell me?

Insights gleaned using voice analytics can serve a variety of purposes for call centers, including:

  • Why people call your contact center and how you can respond effectively to their needs.
  • Which of your call agents are performing well, and who needs support or additional training. (These findings may differ markedly from what your quality assurance process tells you).
  • Which areas, when addressed well, will most improve your teams’ effectiveness and the satisfaction of your clients.
  • Relatedly, how and where to improve your training materials and programs.
  • Why customers are put on hold or transferred, and what elements of your process need to be addressed in order to reduce hold times and hold frequency.

How can your business use call center voice analytics?

Once you have all this information, what can you do with it?


  • Using information on why people call and how they respond to different sales and support approaches can help you maximize conversion rates
  • Call center voice analytics software allows you to automate conversation analysis for quality assurance, making it more efficient and producing a more thorough look at how your agents are handling calls.
  • You can also use voice analytics solutions to optimize call scripts by assessing which variants perform better with a group of clients.
  • State and federal laws often certain information to be stated in every call. Contact center voice analytics make managing compliance much easier by allowing you to make sure your agents are using the required language and information.


By making call analysis much more thorough and accurate, and at the same time, much less labor-intensive, contact center voice analytics solutions help contact centers better understand and improve an array of different aspects of their business. These can include areas such as customer experience, quality assurance, employee training and coaching, compliance, and many more.

Older voice analytics processes involved “manual” analysis of recorded calls. This was done by humans rather than computers, and involved transcription of spoken text. It was slow and labor-intensive, and thus only performed on a small sample of call recordings, which means significantly lower accuracy and a higher chance of missing problems that need to be addressed.

Newer, computer-based voice analytics solutions require sophisticated software, as well as computer systems for storing and processing data. This is especially the case with LVCSR solutions; the result, though, is an unparalleled level of accuracy and monitoring.