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Commerical TTS - Google, Amazon, Apple and Microsoft (2010s)
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== Impact == === Microsoft === Although Narrator itself did not become very popular as an accessibility feature, the dominance of Windows in the operating systems market and the dire need for good screen readers manifested a breeding ground for the development of screen readers, in particular the popular Job Access With Speech (JAWS) and NonVisual Desktop Access (NVDA)<ref>https://www.theverge.com/23203911/screen-readers-history-blind-henter-curran-teh-nvda</ref>. This has had an enormous impact on the speech synthesis field for accessibility applications and the computer usage of visually impaired people. === Google === Due to Google Translate and Google Cloud Speech API's positive reactions, the two applications have been used in a variety of research based on speech recognition. Google Translate has the potential to be used as a tool for Self-Directed Language Learning, allowing for a much more accessible way to learn multiple languages.<ref>van Lieshout, C., & Cardoso, W. (2022). Google Translate as a tool for self-directed language learning. http://hdl.handle.net/10125/73460</ref> Google Cloud Speech API has been used and found in comparative experiments where it is tested against other TTS learning models, such as Kaldi,<ref>Kimura, T., Nose, T., Hirooka, S., Chiba, Y., & Ito, A. (2019). Comparison of Speech Recognition Performance Between Kaldi and Google Cloud Speech API. In J.-S. Pan, A. Ito, P.-W. Tsai, & L. C. Jain (Eds.), Recent Advances in Intelligent Information Hiding and Multimedia Signal Processing (pp. 109β115). Springer International Publishing. https://doi.org/10.1007/978-3-030-03748-2_13</ref> as a Bluetooth navigator for special needs individuals,<ref>Barri, E., Gkamas, A., Michos, E., Bouras, C., Koulouri, C., & Salgado, S. A. K. (2020). Text to Speech through Bluetooth for People with Special Needs Navigation.</ref> and for speech recognition application for the speech impaired.<ref>Anggraini, N., Kurniawan, A., Wardhani, L. K., & Hakiem, N. (2018). Speech Recognition Application for the Speech Impaired using the Android-based Google Cloud Speech API. TELKOMNIKA (Telecommunication Computing Electronics and Control), 16(6), Article 6. https://doi.org/10.12928/telkomnika.v16i6.9638</ref> === Apple === Apple has had a substantial impact on the field of speech synthesis, contributing to both the technology's development and its widespread adoption. Through its various product offerings, Apple has brought speech synthesis to the forefront, making it an integral part of modern user interfaces. The introduction of [https://www.apple.com/siri/ Siri], Apple's voice-activated personal assistant, in 2011 marked a significant milestone in promoting speech synthesis and natural language processing to a broader consumer audience. Siri's ability to understand and respond to natural language queries demonstrated a practical application of speech synthesis, setting a precedent for other tech companies to integrate similar functionalities in their offerings<ref>Aron, J. (2011). How innovative is Apple's new voice assistant, Siri?.</ref>. Apple's continuous improvement and integration of speech synthesis in accessibility features like VoiceOver, have been instrumental in aiding individuals with visual impairments or learning disabilities<ref>Sayago, S., & Ribera, M. (2020, December). Apple Siri (input)+ Voice Over (output)= a de facto marriage: An exploratory case study with blind people. In ''Proceedings of the 9th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion'' (pp. 6-10).</ref>. By making speech synthesis a core component of its user experience and accessibility initiatives, Apple has significantly influenced the perception and the technological trajectory of speech synthesis, fostering innovation and setting a benchmark for user-centric design in the tech industry. === Amazon === Amazon's TTS features, especially in the Kindle, expanded accessibility for various user groups. For the visually impaired and those with reading disabilities such as dyslexia, the TTS capabilities of Kindle devices became invaluable, allowing for auditory consumption of textual content<ref>Schneps, M. H., Thomson, J. M., Sonnert, G., Pomplun, M., Chen, C., & Heffner-Wong, A. (2013). Shorter lines facilitate reading in those who struggle. PloS one, 8(8), e71161.</ref>. This aligned with a broader trend where TTS technologies were increasingly recognized for their potential to bridge accessibility gaps in education<ref>Wood, E., Willoughby, T., Rushing, A., Bechtel, L., & Gilbert, J. (2005). Use of computer input devices by older adults. Journal of Applied Gerontology, 24(5), 419-438.</ref>. With Alexa and the Amazon Echo's ecosystem, voice-driven shopping emerged as a new trend. Users could conduct transactions, reorder products, and get product recommendations using voice commands. This introduced a more intuitive and hands-free shopping experience, evolving the e-commerce landscape<ref>https://searchengineland.com/survey-alexa-frequently-used-assistant-cortana-seen-accurate-269052</ref>. The widespread adoption of Alexa and other voice-enabled devices brought forth concerns regarding data security and user privacy. There were rising questions about how voice data was stored, processed, and potentially utilized, sparking debates about user consent and the ethics of voice data collection<ref>Martin, K. (2019). Ethical implications and accountability of algorithms. Journal of business ethics, 160, 835-850.</ref>.
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