Unveiling the Voice of Your Customers: Speech Analytics Software Explained

Speech analytics software, often known as word detection tools or audio mining software, was previously used to track words and phrases for security purposes. The technique would allow users to process audio and video files with a vast vocabulary recognizer and convert speech to text while identifying pre-defined words or phrases with a moderate accuracy rate. With the application of phonetics-based technology, the accuracy of the speech analytics solution has lately increased significantly. The phonetic-based search allows users to find words, phrases, names, and sentences that were not previously recorded in the dictionary database.

Depending on the primary goal, speech analytics employs a three-step process: processing, transcription, and analysis of customer conversations. Data processing includes combining discussions from recorded audio and voice-over-internet protocol (VoIP) streams. It also collects information about the agents that handled the conversation, the customer's details, and the date and time of the conversation. The data is subsequently transcribed using voice recognition software, which translates sound into text.

Speech analytics analyzes human voice using modern AI technologies such as automatic speech recognition (ASR), natural language processing (NLP), machine learning (ML), transcription, tonality-based sentiment analysis, and algorithms. Speech analytics uses audio data from recorded and live voice calls to detect client sentiment, which ranges from positive to neutral to negative. Simultaneously, speech analytics conceals sensitive data, such as credit card numbers, social security numbers, and other personally identifiable information, to ensure regulatory compliance. The final stage involves detailed reporting based on the team's established criteria, which include call quality, agent performance, sentiment, compliance monitoring, and trend identification.

This study will address the following key questions:

Is the speech analytics market expanding? What is the speech analytics market's short- and long-term growth potential?

What are the top market drivers and constraints affecting the global Speech analytics market?

What are the main end-user industries for Speech Analytics solutions? Which industries are expected to expand the most throughout the projected period?

Which geographical region has the greatest development potential in the Speech analytics market?

Which consumer categories have the highest use of Speech Analytics solutions?

What are the different deployment options for speech analytics solutions?

Vendors covered in the study:

Almawave, Avaya, CallMiner, Chorus.ai, Cogito, Dialpad, Genesys, Invoca, NICE, OpenText, Plum Voice, Prodigal, Qualtrics, Salesken, Talkdesk, Tethr, and Verint.