Introduction of Voice Assistants: Difference between revisions

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== Historical Context ==
== Historical Context ==
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== 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.<ref>Hoy, M. B. (2018). Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants. ''Medical Reference Services Quarterly'', ''37''(1), 81–88. <nowiki>https://doi.org/10.1080/02763869.2018.1404391</nowiki></ref> 


== Key Innovations ==
The foundation of modern voice assistants is rooted in the advancements of speech recognition technology, a field that has been evolving for several decades. <ref>https://voicebot.ai/voice-assistant-history-timeline/</ref> 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.<ref>https://tech-stack.com/blog/how-nlp-improves-multilingual-text-to-speech-voice-assistants/</ref> 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 behavior.<ref>Völkel, S. T., Kempf, P., & Hussmann, H. (2020, July). Personalised chats with voice assistants: The user perspective. In ''Proceedings of the 2nd Conference on Conversational User Interfaces'' (pp. 1-4).</ref>
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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.<ref>Voice Assistants in 2023: Usage, growth, and future of the AI voice assistant market. (2023, January 13). ''Insider Intelligence''. <nowiki>https://www.insiderintelligence.com/insights/voice-assistants/</nowiki></ref> 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 ==
'''Impact on the field'''


Voice Assistants are in most of our daily used devices, such as a smartphone, laptop and speakers. Users can ask the same question in different ways, for example: “What is my name?”, “Do you know what my name is?”, “What would my name be?”. All these questions trigger the expected response. This is because these Voice Assistants use Natural Language processing and speech recognition technologies. This has been improved over the years, which has been discussed in the historical context.
=== Impact on other industries ===
 
=== Impact on individual lives ===


The first consumer-oriented voice recognition system was '''Dragon Dictate.''' This program had some recognition difficulties but later on these were overcome, which is where the first Voice Assistants were created. The first Voice Assistant as we know them today was Apple’s Siri. First, this was an app, but later built into iOS software in 2011. Later on, different companies also started to create their own Voice Assistant. Each assistant is unique, but the core functions are the same, which means that the technology behind speech recognition is similar to all the different assistants. Matthew B. Hoy (2018) There is this ‘competition’ that when one thing is created, other companies will create or improve an even better version than the original. So when the Voice Assistants made their debut, other tech companies created or improved their own Voice Assistant to take the lead in this new field of interacting with a computer. The past few years since Voice Assistants are in our smartphones, more devices have built in speech recognition, for example in cars.
== Criticism ==


'''Security and privacy'''
=== Security concerns ===


There also have been some issues regarding the security and privacy of Voice Assistance. Users can ask to read out loud their personal information, emails, calendar contents, etc. To prevent other people from asking about personal details, Google upgraded its Voice Assistant software to include voice printing, which identifies each user by voice. There have been some cases where anyone from outside could unlock someone’s house by asking Siri to unlock the door. Matthew B. Hoy (2018) The voice prints can also be used to recognize an individual’s unique voice in cases of fraud or theft. <nowiki>https://core.ac.uk/download/pdf/11783663.pdf</nowiki> Amazon’s Alexa had a voice passcode that was introduced to confirm purchases.
=== Privacy issues ===


Voice Assistants are also vulnerable to attacks, like commands that are delivered at ultrasonic frequencies. For example, a product advertisement on television that has embedded ultrasound commands can add items to your shopping list.  
=== 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.<ref name=":0">Phan, T. (2017). The Materiality of the Digital and the Gendered Voice of Siri. ''Transformations'', ''29'', 23–33.</ref> 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.


Also, do these devices always listen? They have to respond by specific cues, so in fact they always need to listen. According to Amazon, Apple and all other tech companies, they insist that all of their devices are not recording the users, only when the user speaks the command to activate the Voice Assistant. Even if the companies are being really careful creating these Assistance, there is a chance of sending the recordings to the company’s server.  
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'.<ref>Fisher, E. (2021). ''Gender Bias in AI: Why Voice Assistants are Female''. Adapt. <nowiki>https://www.adaptworldwide.com/insights/2021/gender-bias-in-ai-why-voice-assistants-are-female</nowiki></ref> 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.<ref name=":0" /><ref>West, M., Kraut, R., & Ei Chew, H. (2019). I'd blush if I could: closing gender divides in digital skills through education.</ref>
 
== Future Research ==


'''Application in various industries'''
== LLM Review ==
[[Large language models (LLM)]] were emplyed in reviewing the current article, as a tool to ensure information accessibility, adherance to grammar rules, coherency, and coesion of information. The tools used to these ends were [[ChatGPT]] and [[Grammarly]].


As I already mentioned, Voice Assistants are used in our daily life. Here there are different categories, such as music, hands free search and other uses of Voice Assistants. This categorie is mostly used to ask for jokes <nowiki>https://dl.acm.org/doi/10.1145/3311956</nowiki>. It is also used to help people who have a disability to read and help people to understand the prescriptions. Also, for people who are blind and there is not a braille text available. Also, 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. (HOY) 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. <nowiki>https://www.nature.com/articles/s41746-020-00332-0</nowiki>
=== 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<ref><nowiki>https://chat.openai.com</nowiki></ref>, using the following prompts:


== Future Research ==
* 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.
Text Text Text Text Text Text Text Text Text Text Text Text


== Notes ==
== Notes ==


== References ==
== References ==
<references />
== Group members ==
Alice


== LLM Review ==
Amber


== Group members ==
Maria Tepei
Alice, Amber, Maria

Revision as of 17:50, 19 September 2023

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 (Oxford Learners Dictionary). 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 lives, present in nearly every personal and home device.

Historical Context

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.[1]

The foundation of modern voice assistants is rooted in the advancements of speech recognition technology, a field that has been evolving for several decades. [2] 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.[3] 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 behavior.[4]

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.[5] 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

Impact on individual lives

Criticism

Security concerns

Privacy issues

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.[6] 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'.[7] 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.[6][8]

Future Research

LLM Review

Large language models (LLM) were emplyed in reviewing the current article, as a tool to ensure information accessibility, adherance to grammar rules, coherency, and coesion 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[9], 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

References

  1. Hoy, M. B. (2018). Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants. Medical Reference Services Quarterly, 37(1), 81–88. https://doi.org/10.1080/02763869.2018.1404391
  2. https://voicebot.ai/voice-assistant-history-timeline/
  3. https://tech-stack.com/blog/how-nlp-improves-multilingual-text-to-speech-voice-assistants/
  4. Völkel, S. T., Kempf, P., & Hussmann, H. (2020, July). Personalised chats with voice assistants: The user perspective. In Proceedings of the 2nd Conference on Conversational User Interfaces (pp. 1-4).
  5. Voice Assistants in 2023: Usage, growth, and future of the AI voice assistant market. (2023, January 13). Insider Intelligence. https://www.insiderintelligence.com/insights/voice-assistants/
  6. 6.0 6.1 Phan, T. (2017). The Materiality of the Digital and the Gendered Voice of Siri. Transformations, 29, 23–33.
  7. Fisher, E. (2021). Gender Bias in AI: Why Voice Assistants are Female. Adapt. https://www.adaptworldwide.com/insights/2021/gender-bias-in-ai-why-voice-assistants-are-female
  8. West, M., Kraut, R., & Ei Chew, H. (2019). I'd blush if I could: closing gender divides in digital skills through education.
  9. https://chat.openai.com

Group members

Alice

Amber

Maria Tepei