From 15de20225af0d0a1a5175d51c0ff8012b0fae93d Mon Sep 17 00:00:00 2001 From: james Date: Tue, 22 Sep 2020 09:17:16 +0000 Subject: [PATCH] Update 'content/topic/(against)-the-coming-world-of-listening-machines.md' --- ...gainst)-the-coming-world-of-listening-machines.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/content/topic/(against)-the-coming-world-of-listening-machines.md b/content/topic/(against)-the-coming-world-of-listening-machines.md index 08438e7..5048e3b 100644 --- a/content/topic/(against)-the-coming-world-of-listening-machines.md +++ b/content/topic/(against)-the-coming-world-of-listening-machines.md @@ -10,7 +10,7 @@ has_experiments: ["living-with-a-black-box.md", "imagine-a-machine-listening-uto ![Automatic speech recognition](audio:static/audio/kathy-reid-intro-to-ASR.mp3),[^kathy_audio_1] transcription and translation {{< nosup >}}[[i](https://www.statnews.com/2020/05/22/ai-startup-transcribes-annotates-doctor-visits-for-patients/ "AI startup transcribes and annotates doctor visits for patients"), [ii](https://www.iflytek.com/en/products/#/Home "iFlyTek: Create a better world with A.I."), [iii](https://www.wired.com/story/iflytek-china-ai-giant-voice-chatting-surveillance/ "How a Chinese AI Giant Made Chatting—and Surveillance—Easy")]{{< /nosup >}} - targeted key word detection {{< nosup >}}[[i](https://theintercept.com/2015/05/05/nsa-speech-recognition-snowden-searchable-text/ "How the NSA Converts Spoken Words Into Searchable Text")]{{< /nosup >}} - -vocal biometrics and audio fingerprinting {{< nosup >}}[[i](https://www.nice.com/engage/real-time-technology/voice-biometrics/ "NICE leverages voice biometrics for safer and more secure customer authentication"), [ii](https://www.acrcloud.com/audio-fingerprinting/ "What Is Audio Fingerprinting?")]{{< /nosup >}} - +vocal biometrics and audio fingerprinting[^li and mills] {{< nosup >}}[[i](https://www.nice.com/engage/real-time-technology/voice-biometrics/ "NICE leverages voice biometrics for safer and more secure customer authentication"), [ii](https://www.acrcloud.com/audio-fingerprinting/ "What Is Audio Fingerprinting?")]{{< /nosup >}}- speaker identification, differentiation, enumeration and location {{< nosup >}}[[i](https://theintercept.com/2018/01/19/voice-recognition-technology-nsa/ "Finding Your Voice"), [ii](https://patents.google.com/patent/US20100235169A1/en "Google Speech differentiation Patent")]{{< /nosup >}} - personality and emotion recognition {{< nosup >}}[[i](https://www.youtube.com/watch?v=86I3-VYIvAM "callAIser in action: Call Center agent gets desperate over angry customer")]{{< /nosup >}} - accent identification {{< nosup >}}[[i](https://www.theverge.com/2017/3/17/14956532/germany-refugee-voice-analysis-dialect-speech-software "Germany to use voice analysis software to help determine where refugees come from")]{{< /nosup >}} - @@ -22,11 +22,11 @@ audio event analysis[^Virtanen] - audio context awareness {{< nosup >}}[[i](https://ieeexplore.ieee.org/document/1285814 "Audio-based context awareness acoustic modeling and perceptual evaluation")]{{< /nosup >}} - music mood analysis {{< nosup >}}[[i](https://www.semanticscholar.org/paper/Multi-Modal-Non-Prototypical-Music-Mood-Analysis-in-Schuller-Weninger/ed0c10ca76ea8ee17514fa569ddf9d0ac7c3a6d5 "Multi-Modal Non-Prototypical Music Mood Analysis in Continuous Space: Reliability and Performances")]{{< /nosup >}} - music identification {{< nosup >}}[[i](https://www.shazam.com/ "Shazam: Name any song in seconds")]{{< /nosup >}} - -music playlist generation - -audio synthesis - +music playlist generation[^Seaver] - +audio synthesis {{< nosup >}}[[i](https://paperswithcode.com/task/audio-generation "Audio Generation")]{{< /nosup >}} - speech synthesis {{< nosup >}}[[i](https://deepmind.com/blog/article/wavenet-generative-model-raw-audio " WaveNet: A generative model for raw audio "), [ii](https://cloud.google.com/text-to-speech " Convert text into natural-sounding speech using an API powered by Google’s AI technologies."), [iii](https://www.descript.com/lyrebird "Lyrebird AI Using artificial intelligence to enable creative expression.")]{{< /nosup >}} - -musical synthesis - +musical synthesis {{< nosup >}}[[i](https://openai.com/blog/jukebox/ "Jukebox, a neural net that generates music")]{{< /nosup >}} - adversarial music {{< nosup >}}[[i](https://arxiv.org/abs/1911.00126 "Real World Audio Adversary Against Wake-word Detection System")]{{< /nosup >}} - brand sonification {{< nosup >}}[[i](https://www.audioanalytic.com/brand-sonification-power-recognising-sounds-brands/ "RBrand sonification: The power of recognising the sounds of brands")]{{< /nosup >}} - aggression detection {{< nosup >}}[[i](https://www.soundintel.com/products/overview/aggression/ "Deterring and Preventing Assault"), [ii](https://www.audeering.com/what-we-do/automotive/ "Cars take care of their passengers")]{{< /nosup >}} - @@ -65,7 +65,7 @@ oral hygiene {{< nosup >}}[[i](https://www.mediapost.com/publications/article/35 disability services - grocery store wayfinding {{< nosup >}}[[i](https://edition.cnn.com/2020/08/27/business/amazon-fresh-first-grocery-store/index.html "Alexa, what aisle is the milk in?")]{{< /nosup >}} - ambient elderly monitoring {{< nosup >}}[[i](https://get.cherryhome.ai/care/ "Cherry Home")]{{< /nosup >}} - -baby monitoring - +baby monitoring {{< nosup >}}[[i](https://www.washingtonpost.com/technology/2020/02/25/ai-baby-monitors/ "AI baby monitors attract anxious parents: ‘Fear is the quickest way to get people’s attention’")]{{< /nosup >}}- house arrest monitoring {{< nosup >}}[[i](https://www.shadowtrack.com/about_us/security/ "VOICE BIOMETRICS FOR HOUSE ARREST MONITORING")]{{< /nosup >}} - ![human rights monitoring](audio:static/audio/intro-to-pulse-and-radio-content-analysis.mp3)[^andre_audio_1] - remote education and proctoring {{< nosup >}}[[i](hhttps://www.freep.com/story/news/education/2020/07/28/michigan-online-bar-test-michigan/5518279002/ "Michigan’s online bar exam testers worry software tracks eye movements, noises")]{{< /nosup >}}- @@ -120,6 +120,7 @@ Another response would be to say that when or if machines listen, they listen ![ [^Cella, Serizel, Ellis]: ![](bib:7c769ce6-5e9e-40d3-96ef-1838a7f57365) [^Alper]: Meryl Alper, *Giving Voice: Mobile Communication, Disability*, and Inequality (MIT Press, 2017) [^Rowe, Maier]: LIBRARY Rowe; Stefan Maier: [*Machine Listening*](https://technosphere-magazine.hkw.de/p/Machine-Listening-kmgQVZVaQeugBaizQjmZnY), Technosphere Magazine (2018) +[^li and mills]: LIBRARY Xiaochang Li and Mara Mills, "Vocal Features: From Identification to Speech Recognition by Machine" 60(2) *Technology and Culture* (2019) pp.129-S160 DOI: https://doi.org/10.1353/tech.2019.0066 [^intelligent_audio_analysis]: ![](bib:827d1f44-5a35-4278-a527-4df67e5ba321) [^Virtanen]: LIBRARY Virtanen et al, *Computational Analysis of Sound Scenes and Events* (Springer, 2017) [^Lei_Mak]: LIBRARY Lei and Mak, "Robust scream sound detection via sound event partitioning" @@ -127,6 +128,7 @@ Another response would be to say that when or if machines listen, they listen ![ [^airplanes]: ![](bib:6676af8a-7a4d-4aa8-af96-f26452f58753) [^kathy_audio_1]: Interview with [Kathy Reid](https://blog.kathyreid.id.au) on August 11, 2020 [^andre_audio_1]: Interview with [André Dao](https://andredao.com/) on September 4, 2020 +[^Seaver]: LIBRARY Nick Seaver "Captivating algorithms: Recommender systems as traps" 24(4) *Journal of Material Culture* (2018), 421-436 [^exemplary projects]: See for instance [Data 4 Black Lives](https://d4bl.org/programs.html), [Feminist Data Manifest-No](https://www.manifestno.com/) [add] [^Crawford and Joler]: ![](bib:3f8dd486-3e28-45ef-929f-65086850870e) [^Goldenfein]: LIBRARY Jake Goldenfein, *Monitoring Laws: Profiling and Identity in the World State* (Cambridge University Press, 2019) https://doi.org/10.1017/9781108637657