August 02, 2011
How NLP and IVR Work Together
NLP stands for “natural language processing,” and its technological development has had a heavy hand in the last several decades of the progression of the interactive voice response (IVR) industry. The IVR experts at Plum Voice recently explored this topic as it pertains to the history of voice recognition, and the expansion of voice technologies in general.
Traditionally, all interactions between computers and human languages are encompassed in the term “NLP,” and IVR and speech recognition software are functions of the overarching NLP technology.
In an informative blog post, Plum’s experts noted that NLP is “generally recognized to have originated in the 1950s, when scientists developed methods to test a computer’s ability to impersonate a human in real time.”
While “speech recognition is considered the opposite of text-to-speech,” the blog mentioned, speech recognition is also one of the only technologies that employs NLP. NLP software can also be incorporated into automatic translations of text from one language to another, answering human-language questions, and automatic summarization which just means the summary of readable text.
These tools have been essential in the development of voice recognition technology and IVR. IVR applications do not necessarily have to include all of the aforementioned technologies, but they are key features that have helped in the progression of voice recognition software as a whole.
NLP also has other uses, particularly when it comes to search functions. “One practical use for NLP as documented by the Belgian technology consulting firm, Nmahn, is to conduct searches of both the Internet and computer databases,” Plum’s blog stated.
It continued, “Many search engines rely on Boolean searches to increase their searches. Boolean searches are typically defined as ones that have tow data values that are true or false. However, most search engines today are powered by NLP as opposed to Boolean, giving users what is traditionally thought of as a more friendly search engine experience.”
Juliana Kenny graduated from the University of Connecticut with a double degree in English and French. After managing a small company for two years, she joined TMC (News - Alert) as a Web Editor for TMCnet. Juliana currently focuses on the call center and CRM industries, but she also writes about cloud telephony and network gear including softswitches.
Edited by Carrie Schmelkin