Introductory Chapter: Virtual Assistants

*Ali Soofastaei*

## **1. Introduction**

The application of Virtual Assistants (VAs) is growing fast in our personal and professional life. It has been predicted that 25% of households using a VA will have two or more devices by 2021 [1]. A virtual assistant is an intelligent application that can perform tasks or provide services for a person responding to orders or inquiries. Some VAs can understand and respond to human speech using synthesized voices. Users may use voice commands to request their VA to answer the questions, manage home appliances, control media playing, and handle other essential activities like email, creating the actions lists, and organize the meetings on calendars [2]. In the Internet of Things (IoT) world, an VA is a popular service to communicate with users based on voice command.

VA capabilities and usage are rapidly rising, thanks to new technologies reaching the people's requirements and a robust focus on voice user interfaces. Samsung, Google, and Apple each have a considerable smartphone user base. Microsoft's Windows-based personal computers, smartphones, and smart speakers have an intelligent VA installed base. On Amazon, smart speakers have a sizable installed base [3]. Over 100 million people have used Conversica's short message and email interface Intelligent Virtual Assistants (IVAs) services in their companies.

Famous virtual assistants like Amazon Alexa and Google Assistant are typically cloud-based for maximum performance and data management. Many behavioral traces, including the user's voice activity history with extensive descriptions, can be saved in a VA ecosystem's remote cloud servers during this process.

The VAs story started in the 1910s, and the growth of technology has supported VAs' improvement. The application of Artificial Intelligence (AI) also was a turning point in VAs journey. Using AI to develop the VAs was a great jump to increase the VAs' capabilities. Currently, VAs use narrow AI with limited options. However, using general AI in the near future can be a revolution to improve the quality of VAs' services.

### **2. Backgrounds**

#### **2.1 Investigational years: 1910s: 1980s**

In 1922, an interesting toy named Radio Rex was introduced that was the first voice-activated doll [4]. A toy in the dog shape would appear from its den the moment it was given a name.

Bell Labs introduced the "Audrey," which was an Automatic Digit Identification device in 1952. It took up a six-foot-high relay rack, used much power, had many wires, and had all of the issues that come with complicated vacuum-tube

electronics. Despite this, Audrey was able to discriminate between phonemes, which are the basic components of speech. However, it was restricted to precise digit identification by assigned speakers. As a result, it may be utilized for voice dialing. However, push-button dialing was generally less expensive and faster than pronouncing the digits in order [5].

Another early gadget that could carry out digital language identification was Shoebox voice-activated calculator that IBM developed. It was revealed to the public for the period of the 1962 Seattle World's Fair after its first market debut in 1961. This initial machine, which was built nearly twenty years earlier than the first Personal Computer made by IBM and debuted in 1981, was capable of detecting sixteen verbal phrases and the numbers 0 through 9.

ELIZA, the first Natural Language Processing (NLP) application or chatbot, was invented by MIT in the 1960s. ELIZA was designed in order to "show that manmachine interaction is essentially superficial" [6]. It applied configuration matching and replacement procedures in written reactions to simulate conversation, creating the impression that the machine understood what was being said.

The ELIZA was designed by professor Joseph Weizenbaum. During the ELIZA development period, Joseph's assistant has requested that he leave the room so that she and ELIZA can chat. Professor Weizenbaum later remarked, "I had no idea that brief exposures to a really simple computer software might cause serious delusional thinking in otherwise normal people [7]." The ELIZA impact, or the tendency to instinctively believe machine activities are equal to people's behaviors, was called after this. Anthropomorphizing is a phenomenon that occurs in human interactions with VAs.

When DARPA funded a five-year Speech Understanding Research effort at Carnegie Mellon in the 1970s, the goal was to reach a vocabulary of 1,000 words. Participants included IBM, Carnegie Mellon University (CMU), and Stanford Research Institute, among many others.

The result was "Harpy," a robot that could understand speech and knew around 1000 words, roughly equivalent to a three-year vocabulary. To reduce voice recognition failures, it could also analyze speech that followed pre-programmed vocabularies, pronunciations, and grammatical patterns to determine which word sequences made sense when spoken.

An improvement to the Shoebox was released in 1986 with the Tangora, a speech recognition typewriter. With a vocabulary of 20,000 words, it was able to anticipate the most likely outcome based on its information. Because of this, it was given the name "Fastest Typewriter. As part of its digital signal processing, IBM used a Hidden Markov model, which integrates statistics into the Using this strategy, you may anticipate which phonemes will follow a given phoneme. However, every speaker was responsible for training the typewriter to recognize his or her voice and halt in.

#### **2.2 The beginning of intelligent virtual assistants: 1990s: Present**

To compete for customers in the 1990s, companies such as IBM, Philips, and Lemont & Hauspie began integrating digital voice recognition into personal computers. The first smartphone introduced in 1994, the IBM Simon laid the groundwork for today's smart virtual assistant.

In 1997, Dragon's Biologically Talking application was able to detect and transcribe natural human speech at a pace of 100 words per minute, with no gaps between syllables. Biologically Talking is still accessible for download, and many doctors in the United States and the United Kingdom continue to use it to keep track of their medical records.

*Introductory Chapter: Virtual Assistants DOI: http://dx.doi.org/10.5772/intechopen.100248*

In 2001, Colloquies released Smarter Child on AIM and MSN Messenger, among other platforms. "Smarter Child" can play games and check the weather as well as seek up data. It can even speak with others to a certain extent, even if it is text.

Siri, which debuted on October 4, 2011, as an option of the iPhone 4S, was the first innovative digital VA to be placed on a smartphone [8, 9]. Siri was built when Apple Inc. purchased Siri Inc. in 2010, a spin-off of SRI International, a research institute financed by DARPA and the US Department of Defense [10]. It was created to make texting, making phone calls, checking the weather, and setting the alarm easier. In addition, it can now make restaurant recommendations, perform Internet searches, and offer driving directions.

Amazon debuted Alexa alongside the Echo in November 2014. Later, in April 2017, Amazon launched a facility that allows users to create conversational interfaces for any VA or interface.

From 2017 till 2021, all the VAs mentioned above have been developed, and there are the more intelligent VAs using for individuals and professional activities. The companies in different areas use the VAs to improve the quality of their decisions at different levels, from operation to the high management level.
