Remove Engineering Remove Machine Learning Remove Text Analytics
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AI and Real-Time Tech vs. Traditional CX Surveys: Who Will Win the Upcoming Battle?

eglobalis

Using natural language processing (NLP) and machine learning, companies can interpret the tone and emotion behind customer interactions on a massive scale. Beyond call centers , text analytics is helping firms decode sentiment across channels. Instead of explicitly asking How do you feel?,

AI 326
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Text Analytics vs Sentiment Analysis: Key Differences & Applications

SurveySensum

While both deal with analyzing text, they serve different purposes. First, What is Text Analytics? Text analysis , also known as text mining, is the process of extracting useful information from unstructured text data. Lets discuss the key differences and applications of sentiment analysis vs text analytics.

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Current Status of Speech (and Text) Analytics

DMG Consulting

Current Status of Speech (and Text) Analytics. Interaction analytics removes the mystery from customer conversations. And due to technical and operational innovations, many IA vendors are replacing their transcription engines with newer and more effective ones that improve the effectiveness of their own offerings.

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Machine Learning Development: A Comprehensive Review of Booktest and Testing Tools

Lumoa

We’re tackling a complex yet crucial topic in machine learning and AI development. Meanwhile, you can almost hear the prudent software engineers screaming: “This is not a process!” This iterative approach doesn’t always fit into the linear development pipelines that software engineers are accustomed to.

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Sentiment Analysis: Guide to Boost CX & Drive Business Insights

SurveySensum

Sentiment analysis is the process of analyzing open-ended feedback using AI technologies like natural language processing, machine learning, and text analytics. It is part of a great umbrella of text mining called text analysis. There are specific Machine Learning algorithms that are used for this purpose.

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Speech Analytics and AI Is a Winning Combination

DMG Consulting

Speech analytics is getting a new lease on life courtesy of artificial intelligence (AI), machine learning, and the digital transformation. Vendors in most IT sectors claim to provide AI-enabled solutions, and the speech analytics providers are no exception. The future of this process is analytics-enabled QM (AQM).

AI 48
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Scouting Report: Speech Analytics Enters Its Next Act — Maturity

DMG Consulting

The primary issues are these: Speech analytics is not yet considered a “must-have” application; analytics-enabled quality assurance (AQA) has not caught on; real-time speech analytics has a limited number of use cases; and text analytics continues to struggle to be noticed. AI AND INTERACTION ANALYTICS.