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AI and Communication: Machines That Can 'Hear' and 'Understand' Voices

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September 10, 2021
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September 10, 2021
AI and Communication: Machines That Can 'Hear' and 'Understand' VoicesAI and Communication: Machines That Can 'Hear' and 'Understand' Voices

Machine learning is one of the most important and powerful types of AI. Blind straight algorithms can never be as beneficial for businesses and society as the ones that can learn and adapt to inputs and trends.

The data generated every day is so massive that no imaginable manpower can comprehend it and turn it into valuable and applicable insights without the help of smart machines. To give an idea, IDC estimated that the digital universe is doubling its size yearly and would reach 44 ZB in 2020 from 4.4 ZB of data generated in 2013. It also forecasted that the big data technology and services market will grow at a 26.4% compound annual growth rate to $41.5 billion through 2018, or about six times the growth rate of the overall information technology market. The ability to draw insights and the ability to optimally monetize available data would place companies in a unique position challenging established rules and processes.

There is already a range of successful FinTech players applying machine learning for better service and higher efficiency. Many startups have disrupted the FinTech ecosystem with machine learning as their key technology.

Having explored the ways FinTech companies are applying machine learning, let’s look at the kitchen – the companies enabling those opportunities. There is a range of software moguls dedicated to enabling machines to do amazing work fast and efficiently.

Earlier this month, HBR published an insightful article authored by H. James Wilson, Sharad Sachdev, and Allan Alter on the ways companies are using machine learning to get faster and more efficient.

One of the greatest applications of machine learning in the banking industry has enabled financial institutions inherently heavy on paperwork to let machines bring paper to digital. Scanning images, understanding voices, and text are one of the most complex tasks to teach a machine.

This time, we will look at companies enabling organizations to automate vocal communication. Powerful solutions apply NLP technology for machines to hear and understand voices. Given that in the coming years, video banking will be paying tribute to traditional branches, voice scanning will be an important part of the service to enhance operations.

AI and Communication: Machines That Can 'Hear' and 'Understand' Voices

One of the examples of companies teaching machines to understand a speech is Sensory. Sensory’s NLP-5x is designed to offer advanced speech recognition, text-to-speech (TTS), high-quality music and speech synthesis, and robotic control to cost-sensitive, high-volume products. The company offers a range of solutions for voice recognition applications. TrulyHandsfree Voice Control Phrase spotting of multiple commands or keywords embedded in speech allows the TrulyNatural, BlueGenie, and NLP-5x to continuously listen for triggers or commands, even in the presence of high noise.

AI and Communication: Machines That Can 'Hear' and 'Understand' Voices

LumenVox is a provider of PC-based speech systems for businesses, distributors, and service providers. LumenVox’s core Speech Software is certified as one of the most accurate, natural-sounding, and reliable solutions in the industry. The Speech Recognizer, Text-to-Speech Server, and Speech Tuner are the foundations of the solution that the company offers. LumenVox’s technology provides tools for companies to effectively connect and communicate with users/clients, increase user satisfaction, and improve employee productivity. Companies like Verizon, GM, Toyota, Kmart, the Aussie Post, British Telecom, government agencies, over 300 banks, telecom service providers, 511 operations, and nearly 2,000 other resellers and developers use LumenVox’s software.

AI and Communication: Machines That Can 'Hear' and 'Understand' Voices

Another machine to understand speech was built by Aspect. Aspect Speech and Text Analytics allows companies to understand what's being said during voice calls, text messages, IM chats, and social media interactions so that they can respond in a compelling way – even in real-time. Aspect speech and text analytics solutions combine phonetics with powerful LVCSR (large vocabulary continuous speech recognition) speech analytics for fast and accurate search and categorization that extends to all captured data. Aspect EQ™ Speech Analytics™ and Aspect EQ™ Engagement Analytics™ give companies two powerful tools for understanding the voice of the customer and how it should impact operation to ultimately deliver the highest quality interactions.

AI and Communication: Machines That Can 'Hear' and 'Understand' Voices

[24]7 Speech is a cloud-based speech and multimodal self-service solution. [24]7's natural language technology is enhanced by advanced deep neural networks (DNN) that draw from over 10 billion utterances to make speech recognition more accurate. The company’s natural language spans both speech and text-based interactions to provide a single intelligence layer to derive meaning from what's been said or typed. [24]7’s natural language model can be applied across IVR, mobile apps, and virtual agents to deliver a consistent customer experience and a lower total cost of ownership (TCO).

Certainly, the list of amazing solutions by AI companies can go on. International tech corporations and newcomers are actively experimenting in the field to enhance organizational productivity and user experience.

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