Welcome to the speech analytics software product directory. This product directory contains basic information about speech analytics vendors and products in the speech analytics market. When beginning your speech analytics evaluation, use these resources to help you find the right speech analytics product for your business needs. Listings include: Vendor information, product name and website, short and long product descriptions and pricing details.
Download the speech analytics software product directory
Get an overview of some of the top speech analytics software applications with our interactive product directory. You'll find detailed descriptions of speech analytics vendors and the speech products they offer, as well as an article from call center expert Donna Fluss on selecting the right speech analytics application.
Additional speech analytics software resources:
|Read the top speech analytics software headlines||Find speech analytics software resources in SearchCRM.com's learning center|
|Learn more about speech analytics technology and find out whether or not it's right for your company with these top speech analytics technology headlines. Find out how to get ROI from speech analytics software and more.||Take our speech quiz, read about speech analytics tools in a workforce optimization suite and browse other CRM and call center technology resources for CRM and call center professionals in our learning center.|
|Learn the top benefits of speech analytics for the call center||Discuss CRM software with your peers on IT Knowledge Exchange|
|According to many experts, the market for speech analytics is growing fast, and when used properly, speech analytics technology can give a company a significant advantage. Read about some of the benefits of speech analytics in this special report.||
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Online customer service product directory
Selecting the right speech analytics application
By Donna Fluss, President, DMG Consulting LLC
Speech Analytics—also known as audio mining—is an application used to structure conversations and find embedded information, including customer insights, implicit needs and wants, and the root causes of issues. These applications can also be used to determine how staff complies with scripts and/or regulations. Some speech analytics applications can identify concepts and trends that organizations didn't even know to watch for. When used in the call center, speech analytics enables managers and executives throughout the enterprise to address the issues that generate call volume and to identify competitive challenges and new revenue opportunities.
Speech analytics technology overview
There are six functional components of a speech analytics application:
1. Speech engine: this is the layer that does the initial analysis of the audio stream and converts the data into a file containing a series of phonemes, or a first pass at text transcript.
2. Indexing and analysis layer (augmentation): this software improves the accuracy of the speech engine's output. Its role is to make sense of the findings from the speech engine and to index it for further analysis, queries and ad hoc searching. This is where the tools import data from other telephony and servicing solutions. Most current R&D investment is focused on this area of speech analytics.
3. Query engine: this is a user interface (UI) where end users define their queries and the output that they expect from the speech analytics tool.
4. Search tool (criteria): this tool is used to conduct ad hoc searches on processed audio files or indices; it should be easy to use and allow nested filtering.
5. Reports and dashboards: these are formats for clearly presenting system findings in a flexible, customizable and graphically appealing manner. They allow end users to drill down and filter their results.
6. Business applications: these prepackaged applications can help users quickly realize benefits from speech analytics. Modules are available for root-cause analysis, customer retention, first call resolution (FCR), competitive intelligence, sales and marketing effectiveness, script adherence, collections effectiveness, and so on.
LVCSR VS. phonetics
All speech analytics applications use an underlying speech engine to perform their initial analysis. The two primary types of speech engines are large vocabulary continuous speech recognition (LVCSR) engines and phonetic engines. LVCSR engines depend on a language model that includes a vocabulary/ dictionary for speech-to-text conversion of audio files. The text file is then searched for target words, phrases and concepts. Phonetic-based applications separate conversations into phonemes, the smallest components of spoken language; they then find segments within the long file of phonemes that match a phonetic index file representation of target words, phrases and concepts. Interestingly, part of LVCSR processing involves breaking words down into phonemes, which is one reason why many of the LVCSR vendors now claim to also do a phonetic analysis.
Read the rest of Donna's column by downloading the speech analytics software product directory.