Introduction of Voice Assistants: Difference between revisions
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== Historical Context == | == 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.<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> | |||
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> | |||
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 other industries === | |||
=== Impact on individual lives === | |||
== Criticism == | |||
=== Security concerns === | |||
=== Privacy issues === | |||
Voice | === 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. | |||
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 == | |||
== 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<ref><nowiki>https://chat.openai.com</nowiki></ref>, 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 == | == Notes == | ||
== References == | == References == | ||
<references /> | |||
== Group members == | |||
Alice | |||
Amber | |||
Maria Tepei | |||
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
- ↑ 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
- ↑ https://voicebot.ai/voice-assistant-history-timeline/
- ↑ https://tech-stack.com/blog/how-nlp-improves-multilingual-text-to-speech-voice-assistants/
- ↑ 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).
- ↑ 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/
- ↑ 6.0 6.1 Phan, T. (2017). The Materiality of the Digital and the Gendered Voice of Siri. Transformations, 29, 23–33.
- ↑ 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
- ↑ West, M., Kraut, R., & Ei Chew, H. (2019). I'd blush if I could: closing gender divides in digital skills through education.
- ↑ https://chat.openai.com
Group members
Alice
Amber
Maria Tepei