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Natural Language/Machine Learning/Cognitive Learning

Natural language, machine learning, and cognitive learning are the technologies that underly most Artifical Intelligence applications. Natural Language Processing (NLP) helps computers interpret and manipulate human language; Machine Learning (ML) provides systems the ability to automatically learn and improve without being explicitly programmed. Cognitive Learning (CL) combines ML and NLP. See below for the latest news and trends in NLP, ML, and CL.

Features

Succeeding in the Battle Against Deepfakes

New AI tech is helping detect voice and video fraud attempts.

AI Is Rapidly Automating Audio Content Generation

New solutions lower costs and improve voice quality.

Voice Is Poised to Take a Quantum Leap

Exploring quantum computing's expected impact on the speech technology market.

Eliminate Ambient Noise to Make Speech Recognition More Accurate

Technology is improving speech's ability to hear what is necessary.

Industry Voices

Generative AI Will Redefine Crucial Work Skills, but It Can’t Replace Human Expertise

GenAI signals new possibilities, and it's inevitable that certain tasks will be automated. But humans won't be replaced; instead, their roles will be elevated.

Uncover Hidden Gems in Your CX Data with AI by NICE

The Need for Continuous Speech Recognition Testing

Conversational AI and voice have to be tested to ensure that they work flawlessly.

The Risks Posed by Biases in Voice and AI

Artificial intelligence is still a novel concept with its own unique benefits and flaws. This is how it will integrate into sales, marketing, and customer interactions.

Columns

Customer Experience AI: Will Perception Drive or Deter Adoption?

We've not yet seen the tipping point for customers when it comes to AI in the contact center.

Conversational AI Is Ushering in Huge Contact Center Advances

These solutions are getting better just as self-service becomes a top priority.

AI Can Elevate In-Store Music

So-called elevator music can be jazzed up by genAI, but there are gray areas.

Standards for Openness in AI Models: The Model Openness Framework

Here's how to ensure these tools can be used in mission-critical applications

Natural Language/Machine Learning/Cognitive Learning Companies and Suppliers