Introduction of Voice Assistants

Introduction

A "Voice Assistant" is a computer program that can converse with a human and carry out tasks by following instructions or receiving information through voice commands (from the Oxford Learners Dictionary definition of "Voice assistant"). With the emergence of AI in the last two decades, this type of program has advanced significantly, thanks to technological breakthroughs like Hidden Markov Models, and Neural Networks that have improved their speech recognition capabilities, as well as improvements in audio signal quality. Today, Voice Assistants are an integral part of our daily lives¹, present in nearly every personal and home device.

Key Innovations

The recent development of voice assistants has been driven by key innovations in the field. One significant factor contributing to their widespread adoption is the integration of voice assistants into smartphones and mobile devices, making this technology accessible to a broader audience. Several factors have facilitated this development, including increased computing power, access to extensive linguistic (speech) data, advancements in machine learning, and a deeper understanding of human language in context.

The foundation of modern voice assistants is rooted in the advancements of speech recognition technology, a field that has been evolving for several decades. The origins of this research can be traced back to the 1960s, with notable contributions from companies like IBM. The improvement of speech recognition accuracy through machine learning techniques has enabled the development of voice assistants capable of accurately understanding and interpreting human speech. Additionally, these software systems utilize natural language processing (NLP) to comprehend spoken words and discern the user's intent. Hardware advancements, including miniaturization, microphone enhancements, and the development of compact, low-power processors, have further contributed to the practicality of voice assistants, allowing them to process commands locally. Another crucial aspect introduced by machine learning and data analytics within voice assistants is continuous personalization. This feature offers users a tailored experience by providing personalized recommendations based on individual preferences, interaction history, and behaviour.

Voice assistants have made their way into various industries, with approximately 123.5 million US adults using them monthly. It is anticipated that this number will increase to nearly 49% of US adults over the next three years. These software systems are primarily utilized on smartphones and smart speakers, with Amazon Echo holding a prominent position in the US smart speaker market.

Impact

Impact on other industries

As already mentioned, Voice Assistants are used in our daily lives. Here there are different categories, such as music, hands-free search, and other uses of Voice Assistants. This category is mostly used to ask for jokes. It is also used to help people with reading impairments and help people to understand difficult texts, like prescriptions. Also, for people who are blind and there is not a braille text available. There has been research about people with dementia who can benefit from a voice assistant that can answer the same questions over and over again without losing patience and encourage the patients when needed.  During the Covid-19 pandemic, hospitals were struggling with maintaining inpatient and outpatient services for other healthcare needs. Voice Assistants have been used to deliver healthcare information, which reduced stress on the health system.

Criticism

Gender bias

Voice assistants represent the fundamental departure from earlier technologies relying on sterile, keyword-driven commands typed on a keyboard; instead they harness the power of speech, deemed as the most natural form of human communication. However, an aspect of this transition that has drawn significant criticism from researchers in fields of social studies is the adoption of nurturing, female voices for voice assistants, with a profound impact on how users engage with and perceive them.

The use of female voices has contributed to asistants being seen as friendlier and more familiar to users, making interactions more engaging thanks to the perceived warmth, approachability and their coded 'readiness to help'. While some voice assistants do indeed offer male voice alternatives, it's important to note that the default and most well known voice for all leading voice assistants remains female. Such design choices are sparking discussions about reinforcing and perpetuating gender stereotypes and biases, raising questions about the roles assigned to technology and how these choices can further shape societal perceptions.

Future Research

Already, Voice Assistants can answer a great number of questions and it can also control our homes. But they can also be programmed to guide tours in museums to give information and answer questions. This would be quite appealing for students to encourage them visition exhibitions.

The world has gotten smaller because of the internet which allows us to stay in touch with people from different continents. Google’s assistant can help to translate real-time conversations when a user asks to translate. For now, there are around 40 different languages available, but in the future maybe minority languages will also be recognised and can be translated into any language.

The expected percentage of the population in the US who uses a Voice Assistant will slowly increase. This is a 3-year forecast, so it is not far in the future, but still interesting why this is because the speed of improvements is quite high.

Improving machine learning models requires a lot of personal data. Brands that collect data for these purposes should be transparent and separate this data from data that is sold to advertisers so that users of Voice Assistants can make decisions without the influence of advertisers.

LLM Review

Large language models (LLM) were employed in reviewing the current article, as a tool to ensure information accessibility, adherence to grammar rules, coherency, and cohesion of information. The tools used to these ends were ChatGPT and Grammarly.

ChatGPT

After completing a comprehensive draft of the information to be included in the sections of this page, with the corresponding sources, the sentences were fed into ChatGPT, using the following prompts:

• Go through the following text and identify any incoherences, repetitive information, or convoluted phrases; make sure the text is objective, with a neutral tone, in line with the style of a wikipedia article.

Notes

1. According to Voicebot.ai, 50% of the population use a Voice Assistant, either in their car, at home or through their smartphone. See also Section “Impact in various industries and individuals’ daily life”

Group members

Alice Vanni

Amber Lankheet

Maria Tepei