Artificial Intelligence, Business, Speech Recognition, Technology

Making Natural Language Processing Feasible with Artificial Intelligence

In a past post, we discussed the technological and the financial challenges that go hand-in-hand with developing natural language processing (NLP) applications. While these challenges remain relevant, more recent developments mean it’s easier and less expensive to incorporate natural language processing into your voice channels.

Thanks to artificial intelligence (AI), companies can manage NLP apps more easily and for far less cost. They can do all of this by leveraging APIs for quick, easy access to AI engines. All these factors lower the entry barriers for companies interested in AI and NLP technology.

Enter AI

The big difference-maker here is artificial intelligence. Building and tuning grammars for NLP applications is one of the biggest drains on time and financial resources companies encounter with NLP. AI helps to mitigate that.

AI is able to take natural language phrases and extrapolate from them to figure out what other terms and phrases could work to accomplish the same task. The phrase collection and curation processes are much simpler, too.

Using the AI engine, you can see what input the application collects from real users. These responses can be added or removed from the algorithm the application uses to determine caller intent at your discretion. The more information you feed the AI application, the more accurate it will be.

AI Drives Down Costs

Grammar tuning is one of the most expensive aspects of creating NLP applications. AI reduces the amount of work necessary to get effective results.

Although most companies aren’t looking to dump tens of millions of dollars into NLP applications, the cost to get a good solution that actually works is a barrier for many businesses. Depending on the system, companies can expect to pay $1–2 million per year maintaining grammars for a NLP app.

This isn’t to suggest that AI-powered NLP is cheap. There are still telecom charges and the cost of accessing the AI system. However, it can be far less expensive than the old way of doing thing. AI, therefore, lowers the bar for entry into improve voice channel communications by making NLP more affordable.

APIs – The Right Building Blocks

All of this begs the question, how does a company go about taking advantage of these new developments in relation to AI and NLP? The answer is by using APIs.

APIs aren’t new. But they are the building blocks of the modern digital age in a lot of ways. Thanks to APIs, AI engines (like IBM’s Watson) are exponentially more accessible.

Benefits of NLP and AI in Voice Communications

Providing better customer experiences over the phone is one of the main reasons why companies are interested in NLP. As the first point of contact for many customers, phone menus can be frustrating and time consuming. This doesn’t bode well for customer experience.

Therefore, getting customers to the right people or self-service applications quickly is important for reducing those frustration levels. An AI-powered call-routing application provides this functionality. Instead of sitting through a laundry list of phone tree options, callers can simply say what they want to do and be directed to the right place.

Recent studies suggest that AI-powered call-routing can help reduce call duration by up to 50% and improve contact center productivity by up to 20%. These types of improvements can have a significant effect on customer satisfaction and experience.

 

Here at Plum, we’ve developed an AI-powered call-routing app for our communications platform. It provides companies with an NLP option for their voice channels and offers an easy, convenient point of entry for AI technology.

To learn more about AI and voice communications, check out our AI offerings.

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Jason Myers stitches together letters and words into cogent thoughts as the Copywriter at Plum Voice.

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