Natural Language User Interface: Fundamentals and Applications

By Fouad Sabry

What Is Natural Language User Interface

A natural-language user interface is a sort of computer human interface in which linguistic phenomena such as verbs, phrases, and clauses operate as UI controllers for the purpose of producing, selecting, and changing data in software programs. Natural-language user interfaces are becoming increasingly popular.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Natural-language user interface

Chapter 2: List of artificial intelligence projects

Chapter 3: Natural-language understanding

Chapter 4: Question answering

Chapter 5: Document retrieval

Chapter 6: Outline of natural language processing

Chapter 7: Concept search

Chapter 8: Natural-language programming

Chapter 9: Google Hummingbird

Chapter 10: Query understanding

(II) Answering the public top questions about natural language user interface.

(III) Real world examples for the usage of natural language user interface in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of natural language user interface' technologies.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of natural language user interface.

• Language: English
• Publisher: One Billion Knowledgeable
• Release date: Jul 5, 2023

Book preview

Chapter 1: Natural-language user interface

To create, select, and alter data in applications, natural-language user interface (LUI or NLUI) software employs linguistic phenomena like verbs, phrases, and clauses as UI controls.

Natural-language interfaces are highly desirable in the field of interface design due to their speed and simplicity of use; nonetheless, they often struggle with the difficulties of comprehending several types of confusing input. In natural language processing and computational linguistics, natural-language interfaces are a hot topic. One of the current aims of the Semantic Web is to provide a simple, universal, natural-language interface.

Naturalness of text-based user interfaces varies. Many artificial (formal) programming languages use human-language idioms. The shallow natural-language user interface of a standard keyword search engine is another example.

To put it simply, a natural language search engine would provide more relevant results to user queries (as opposed to keyword search). When asked a query like which U.S. state has the highest income tax? the default behavior of most search engines is to disregard the question and do a search on the terms state, income, and tax. However, natural-language search makes an effort to apply NLP to decipher the question's intent before doing a web search and returning a filtered result set. If this method is successful, the results would be more relevant than those returned by a keyword search engine.

Nl interface prototypes have been around since the late 1960s and early 1970s.

SHRDLU is a block-manipulating, natural-language user interface.

William A. Woods' Lunar is a language-based portal to a database housing chemical analysis of Apollo 11 lunar rock samples.

Using the Prolog database, Chat-80 translated English inquiries into Prolog phrases. Several more experimental Nl interfaces were built off of Chat-80's source code, which was extensively disseminated. The LPA website includes a live demonstration.

ELIZA, created by MIT's Joseph Weizenbaum between 1964 and 1966, acted like a therapist by analyzing user input via scripts. Sometimes, the DOCTOR script generated interaction that was eerily lifelike, despite the fact that it used practically little data on human cognition or emotion. The LPA website includes a live demonstration.

Janus is also unique in that it can answer questions about the past, present, and future.

Trinzic's Brainpower (formed by the merger of AICorp and Aion).

BBN’s Parlance built on experience from the development of the Rus and Irus systems.

IBM Languageaccess

The Symantec FAQ.

Natural Language, Inc.'s Datatalker.

BIM System's Loqui.

Linguistic Technology Corporation's English Wizard.

In the past, consumers have tended to anthropomorphize computers when interacting with them through natural language interfaces. This has resulted in the user having excessively high expectations for the system. The AI winter of the 1970s and 1980s is a cautionary tale about the dangers of setting unrealistic user expectations for a system's capabilities and the subsequent disappointment when the system falls short of those expectations.

One such work, Natural Language Interfaces to Databases - An Introduction, published in 1995, outlines the difficulties inherent in this field:

Modifier attachment

It's unclear what is meant by List all personnel in the organization having a driving license, unless you already know that corporations can't have licenses to operate motor vehicles.

Conjunction and disjunction

If you don't know that a person can't simultaneously reside in two different locations, the instruction List all candidates who live in California and Arizona is unclear.

Anaphora resolution

determine if a self-referential question uses the first person singular or plural.

The speed and efficiency of the interface are two additional, more broad aims to keep in mind; in all algorithms, these two factors are the primary determinants of which approaches are most likely to be commercially successful. Furthermore, additional care must be used when localizing across many language sites due to the fact that most languages have somewhat different rules for sentence construction and grammar.

Finally, the most pressing methodological challenge is developing an all-encompassing algorithm that can identify any human voice, regardless of the speaker's ethnicity, gender, or age. Success requires overcoming the large variations in the retrieved characteristics, even different speakers who use the same word or phrase.

Many different kinds of technology have emerged as a result of the natural-language interface.

The most common applications are:

The most prevalent use of ASR technology nowadays is dictation. This encompasses not just normal word processing but also medical transcriptions, legal and commercial dictation. To improve the system's precision, specialized dictionaries are sometimes employed.

Telemetry, ASR, and Command Command and control systems are computerized infrastructures whose primary purpose is to execute predetermined commands. Simple commands like Open Netscape or Start a new xterm will have the desired effect.

In the field of telecommunications, various PBX and Voice Mail systems let users provide instructions by voice rather than by touching keys to generate different tones.

When it comes to wearables, speech is an obvious option due to the restricted inputs available.

Many individuals have trouble typing because of medical conditions or impairments, including RSI, muscular dystrophy, and other similar conditions. A telephone-connected system, for instance, might transcribe spoken words for the hard-of-hearing.

Some modern smartphones have the capability to recognize commands such as call home with built-in C&C voice recognition software. This has the potential to greatly impact the development of Linux and automated voice recognition.

Some of the programs that make use of natural-language recognition and, thus, include the aforementioned utilities are described and identified below.

The Ubiquity Firefox extension is a set of simple, natural-language-derived commands that combine several online services