107 Matching Annotations
  1. Jul 2020
    1. Defamation law walks a fine line between the right to freedom of speech and the right of a person to avoid defamation. On one hand, a reasonable person should have free speech to talk about their experiences in a truthful manner without fear of a lawsuit if they say something mean, but true, about someone else. On the other hand, people have a right to not have false statements made that will damage their reputation.
    1. when some listeners hear poets read with one or more of these characteristics—slow pitch speed, slow pitch acceleration, narrow pitch range, low rhythmic complexity, and/or slow speaking rate—they hear Poet Voice.”
  2. Jun 2020
    1. Just as journalists should be able to write about anything they want, comedians should be able to do the same and tell jokes about anything they please

      where's the line though? every output generates a feedback loop with the hivemind, turning into input to ourselves with our cracking, overwhelmed, filters

      it's unrealistic to wish everyone to see jokes are jokes, to rely on journalists to generate unbiased facts, and politicians as self serving leeches, err that's my bias speaking

    1. Such is the security of this architecture, that it has prompted law enforcement agencies around the world to complain that they now cannot access a user’s messages, even with a warrant. There is no backdoor—the only option is to compromise one of the endpoints and access messages in their decrypted state.
  3. May 2020
  4. Apr 2020
    1. Python contributed examples¶ Mic VAD Streaming¶ This example demonstrates getting audio from microphone, running Voice-Activity-Detection and then outputting text. Full source code available on https://github.com/mozilla/DeepSpeech-examples. VAD Transcriber¶ This example demonstrates VAD-based transcription with both console and graphical interface. Full source code available on https://github.com/mozilla/DeepSpeech-examples.
    1. Python API Usage example Edit on GitHub Python API Usage example¶ Examples are from native_client/python/client.cc. Creating a model instance and loading model¶ 115 ds = Model(args.model) Performing inference¶ 149 150 151 152 153 154 if args.extended: print(metadata_to_string(ds.sttWithMetadata(audio, 1).transcripts[0])) elif args.json: print(metadata_json_output(ds.sttWithMetadata(audio, 3))) else: print(ds.stt(audio)) Full source code
    1. DeepSpeech is an open source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. NOTE: This documentation applies to the 0.7.0 version of DeepSpeech only. Documentation for all versions is published on deepspeech.readthedocs.io. To install and use DeepSpeech all you have to do is: # Create and activate a virtualenv virtualenv -p python3 $HOME/tmp/deepspeech-venv/ source $HOME/tmp/deepspeech-venv/bin/activate # Install DeepSpeech pip3 install deepspeech # Download pre-trained English model files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.pbmm curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.scorer # Download example audio files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/audio-0.7.0.tar.gz tar xvf audio-0.7.0.tar.gz # Transcribe an audio file deepspeech --model deepspeech-0.7.0-models.pbmm --scorer deepspeech-0.7.0-models.scorer --audio audio/2830-3980-0043.wav A pre-trained English model is available for use and can be downloaded using the instructions below. A package with some example audio files is available for download in our release notes.
    1. Library for performing speech recognition, with support for several engines and APIs, online and offline. Speech recognition engine/API support: CMU Sphinx (works offline) Google Speech Recognition Google Cloud Speech API Wit.ai Microsoft Bing Voice Recognition Houndify API IBM Speech to Text Snowboy Hotword Detection (works offline) Quickstart: pip install SpeechRecognition. See the “Installing” section for more details. To quickly try it out, run python -m speech_recognition after installing. Project links: PyPI Source code Issue tracker Library Reference The library reference documents every publicly accessible object in the library. This document is also included under reference/library-reference.rst. See Notes on using PocketSphinx for information about installing languages, compiling PocketSphinx, and building language packs from online resources. This document is also included under reference/pocketsphinx.rst.
    1. Running the example code with python Run like this: cd vosk-api/python/example wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz tar xf alphacep-model-android-en-us-0.3.tar.gz mv alphacep-model-android-en-us-0.3 model-en python3 ./test_simple.py test.wav To run with your audio file make sure it has proper format - PCM 16khz 16bit mono, otherwise decoding will not work. You can find other examples of using a microphone, decoding with a fixed small vocabulary or speaker identification setup in python/example subfolder
    2. Vosk is a speech recognition toolkit. The best things in Vosk are: Supports 8 languages - English, German, French, Spanish, Portuguese, Chinese, Russian, Vietnamese. More to come. Works offline, even on lightweight devices - Raspberry Pi, Android, iOS Installs with simple pip3 install vosk Portable per-language models are only 50Mb each, but there are much bigger server models available. Provides streaming API for the best user experience (unlike popular speech-recognition python packages) There are bindings for different programming languages, too - java/csharp/javascript etc. Allows quick reconfiguration of vocabulary for best accuracy. Supports speaker identification beside simple speech recognition.
    3. Kaldi API for offline speech recognition on Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
    1. import all the necessary libraries into our notebook. LibROSA and SciPy are the Python libraries used for processing audio signals. import os import librosa #for audio processing import IPython.display as ipd import matplotlib.pyplot as plt import numpy as np from scipy.io import wavfile #for audio processing import warnings warnings.filterwarnings("ignore") view raw modules.py hosted with ❤ by GitHub View the code on <a href="https://gist.github.com/aravindpai/eb40aeca0266e95c128e49823dacaab9">Gist</a>. Data Exploration and Visualization Data Exploration and Visualization helps us to understand the data as well as pre-processing steps in a better way. 
    2. TensorFlow recently released the Speech Commands Datasets. It includes 65,000 one-second long utterances of 30 short words, by thousands of different people. We’ll build a speech recognition system that understands simple spoken commands. You can download the dataset from here.
    3. In the 1980s, the Hidden Markov Model (HMM) was applied to the speech recognition system. HMM is a statistical model which is used to model the problems that involve sequential information. It has a pretty good track record in many real-world applications including speech recognition.  In 2001, Google introduced the Voice Search application that allowed users to search for queries by speaking to the machine.  This was the first voice-enabled application which was very popular among the people. It made the conversation between the people and machines a lot easier.  By 2011, Apple launched Siri that offered a real-time, faster, and easier way to interact with the Apple devices by just using your voice. As of now, Amazon’s Alexa and Google’s Home are the most popular voice command based virtual assistants that are being widely used by consumers across the globe. 
    4. Learn how to Build your own Speech-to-Text Model (using Python) Aravind Pai, July 15, 2019 Login to Bookmark this article (adsbygoogle = window.adsbygoogle || []).push({}); Overview Learn how to build your very own speech-to-text model using Python in this article The ability to weave deep learning skills with NLP is a coveted one in the industry; add this to your skillset today We will use a real-world dataset and build this speech-to-text model so get ready to use your Python skills!
    1. One can imagine that this whole process may be computationally expensive. In many modern speech recognition systems, neural networks are used to simplify the speech signal using techniques for feature transformation and dimensionality reduction before HMM recognition. Voice activity detectors (VADs) are also used to reduce an audio signal to only the portions that are likely to contain speech. This prevents the recognizer from wasting time analyzing unnecessary parts of the signal.
    2. Most modern speech recognition systems rely on what is known as a Hidden Markov Model (HMM). This approach works on the assumption that a speech signal, when viewed on a short enough timescale (say, ten milliseconds), can be reasonably approximated as a stationary process—that is, a process in which statistical properties do not change over time.
    3. The first component of speech recognition is, of course, speech. Speech must be converted from physical sound to an electrical signal with a microphone, and then to digital data with an analog-to-digital converter. Once digitized, several models can be used to transcribe the audio to text.
    4. How speech recognition works, What packages are available on PyPI; and How to install and use the SpeechRecognition package—a full-featured and easy-to-use Python speech recognition library.
    5. The Ultimate Guide To Speech Recognition With Python
    1. At Brown’s sentencing, Judge Lindsay was quoted as saying “What took place is not going to chill any 1st Amendment expression by Journalists.” But he was so wrong. Brown’s arrest and prosecution had a substantial chilling effect on journalism. Some journalists have simply stopped reporting on hacks from fear of retribution and others who still do are forced to employ extraordinary measures to protect themselves from prosecution.
  5. Mar 2020
    1. While Americans tend to prioritize individual liberty, Europeans are more inclined to value the role of the state. Americans are generally more tolerant of offensive speech than Europeans. That has translated to a greater impetus to regulate tech in Europe.
  6. Jan 2020
    1. Many of the book’s essayists defend freedom of expression over freedom from obscenity. Says Rabbi Arthur Lelyveld (father of Joseph, who would become executive editor of The New York Times): “Freedom of expression, if it is to be meaningful at all, must include freedom for ‘that which we loathe,’ for it is obvious that it is no great virtue and presents no great difficulty for one to accord freedom to what we approve or to that to which we are indifferent.” I hear too few voices today defending speech of which they disapprove.

      I might take issue with this statement and possibly a piece of Jarvis' argument here. I agree that it's moral panic that there could be such a thing as "too much speech" because humans have a hard limit for how much they can individually consume.

      The issue I see is that while anyone can say almost anything, the problem becomes when a handful of monopolistic players like Facebook or YouTube can use algorithms to programattically entice people to click on and consume fringe content in mass quantities and that subtly, but assuredly nudges the populace and electorate in an unnatural direction. Most of the history of human society and interaction has long tended toward a centralizing consensus in which we can manage to cohere. The large scale effects of algorithmic-based companies putting a heavy hand on the scales are sure to create unintended consequences and they're able to do it at scales that the Johnson and Nixon administrations only wish they had access to.

      If we look at as an analogy to the evolution of weaponry, I might suggest we've just passed the border of single shot handguns and into the era of machine guns. What is society to do when the next evolution occurs into the era of social media atomic weapons?

    2. McCarthy next asks: “Who selects what is to be recorded or transmitted to others, since not everything can be recorded?” But now, everything can be recorded and transmitted. That is the new fear: too much speech.
  7. Nov 2019
    1. From this perspective, GPT-2 says less about artificial intelligence and more about how human intelligence is constantly looking for, and accepting of, stereotypical narrative genres, and how our mind always wants to make sense of any text it encounters, no matter how odd. Reflecting on that process can be the source of helpful self-awareness—about our past and present views and inclinations—and also, some significant enjoyment as our minds spin stories well beyond the thrown-together words on a page or screen.

      And it's not just happening with text, but it also happens with speech as I've written before: Complexity isn’t a Vice: 10 Word Answers and Doubletalk in Election 2016 In fact, in this mentioned case, looking at transcripts actually helps to reveal that the emperor had no clothes because there's so much missing from the speech that the text doesn't have enough space to fill in the gaps the way the live speech did.

  8. Jul 2019
    1. Refusing advertising is refusing to privilege moneyed speech. The increasing equation of money with speech—that is, those with the most money can be the loudest and most persistent voices in contemporary media—is denied when advertising is refused.
  9. Feb 2019
    1. constantly associating the ideas of articulate sounds

      So those who can speak tend to believe that writing is merely a sign for speech, but both speech and writing are signs for thought.

    2. Cure of those El'ils

      A medicinal model of education. "Hi, I'm Thomas Sheridan. All these dumbasses are hopelessly lost because they don't speak correctly. They'll never do anything good, or see what good is, because bad speech runs rampant. The only hope is to heal them by teaching them to speak well. That is, like me."

    1. Speech and thought arc inseparable, in Vico'., view: They evolve together.

      I would argue that speech, thought, AND writing evolve together.

    2. Speech and thought arc inseparable, in Vico'., view: They evolve together.

      True and not true. I cannot speak a thought to someone else unless I have a word for it. However, I do have thoughts that as yet do not have words. Do we get stuck on thoughts, however, unable to progress onto a successive thought, if the current thought has no name? I don't know, but I think it's an interesting concept to mull over. And, once again, calls to mind the movie Arrival.

    1. Unsupervised speech representation learning using WaveNet autoencoders

      我们通过将自动编码神经网络应用于语音波形来考虑无监督提取有意义的语音潜在表示的任务。目标是学习能够从信号中捕获高级语义内容的表示,例如,音素身份,同时不会混淆信号中的低级细节,例如底层音高轮廓或背景噪音。自动编码器模型的行为取决于应用于潜在表示的约束类型。我们比较了三种变体:简单的降维瓶颈,高斯变分自动编码器(VAE)和离散矢量量化VAE(VQ-VAE)。我们根据说话人的独立性,预测语音内容的能力以及精确重建单个谱图帧的能力来分析学习表征的质量。此外,对于使用VQ-VAE提取的差异编码,我们测量将它们映射到电话的容易程度。我们引入了一种正则化方案,该方案强制表示集中于话语的语音内容,并报告性能与ZeroSpeech 2017无监督声学单元发现任务中的顶级条目相当。 【translated by 谷歌翻译】


      【摘要自机器之心】:

      论文《Unsupervised speech representation learning using WaveNet autoencoders》介绍了通过将自编码神经网络用到语音波形提取语音中有意义的隐藏表征的无监督任务。目的是学习到一种能够捕捉信号中高层次语义内容的表征,同时又能够对有背景噪声或者潜在基频曲线(underlying pitch contour)的信号中的扰乱信息足够稳定。自编码器模型的行为由应用到隐藏表征的约束所决定。在此论文中,作者对比了三种变体:简单降维瓶颈、高斯变分自编码器和离散向量量化VAE。而后,作者对预测语音内容的能力等进行了分析。

  10. Nov 2018
    1. Interpretable Convolutional Filters with SincNet

      一篇值得我高度关注的 paper,来自 AI 三巨头之一 Yoshua Bengio!其背后的核心是将数字信号处理DSP中卷积的激励函数(滤波器)进行了重新设计,不仅会保留了卷积的特性(线性性+时间平移不变性)还在滤波器上添加待学习参数来学习合适的高低频截断位置。

    2. Whispered-to-voiced Alaryngeal Speech Conversion with Generative Adversarial Networks

      这是一篇用 GAN 来做 Voiced Speech Restoration 的,并且使用了作者自己提出的 speech enhancement using GANs (SEGAN) 。

      于我而言,亮点有二:

      1. 数据是时序语音
      2. 利用 GAN 对语音的增强效果似乎对降噪有些启发
      3. 网络结构图画的蛮好看的:

    1. They can spew hate amongst themselves for eternity, but without amplification it won’t thrive.

      This is a key point. Social media and the way it amplifies almost anything for the benefit of clicks towards advertising is one of its most toxic features. Too often the extreme voice draws the most attention instead of being moderated down by more civil and moderate society.

  11. Oct 2018
    1. "I am really pleased to see different sites deciding not to privilege aggressors' speech over their targets'," Phillips said. "That tends to be the default position in so many online 'free speech' debates which suggest that if you restrict aggressors' speech, you're doing a disservice to America—a position that doesn't take into account the fact that antagonistic speech infringes on the speech of those who are silenced by that kind of abuse."
    1. Literary association PEN America has filed a lawsuit against Trump for using government power to harass the press.

  12. Sep 2018
    1. Judas lofted up a word, revealing his courage, and he spoke in Hebrew:

      Judas's prayer in Hebrew. Invokes Scripture: creation, fall of angels

    2. Elene spoke and before those nobles said

      Elene's speech: Hebrew Bible as prophesying Christ

    1. "The ideas of the First Amendment are not designed to deal with what it took to make the materials [of pornography.]" [5:56-5:59]

    2. "The 'freely choosing women'... As if you've raised a freely choosing black person [who decides to 'freely choose'] to clean toilets. That's the equivalent. You call that freedom. It's called freedom when women choose to do it and it's sex because people believe that sex is free. However, pornography is selling yourself for sex. The idea of money is supposed to make it free. Usually, when people have sex with another person and choose to do it, they're not being paid, it's free because you're not being paid. In other words, this is an arm of prostitution." [NOT VERBATIM] [3:53-4:31]

    1. For the longest time, we thought that as speech became more democratized, democracy itself would flourish. As more and more people could broadcast their words and opinions, there would be an ever-fiercer battle of ideas—with truth emerging as the winner, stronger from the fight. But in 2018, it is increasingly clear that more speech can in fact threaten democracy. The glut of information we now face, made possible by digital tools and social media platforms, can bury what is true, greatly elevate and amplify misinformation and distract from what is important.
  13. Aug 2018
  14. Jul 2018
    1. Why didn’t the men begin? What were they waiting for? There they stood, smoothing their gloves, patting their glossy hair and smiling among themselves. Then, quite suddenly, as if they had only just made up their minds that that was what they had to do, the men came gliding over the parquet. There was a joyful flutter among the girls.

      Throughout the story, the narrator figures the men and women as birds participating in courtship/pre-mating dances. Observe the narrator's ornithological language here: the men "glid[e] over the parquet" towards the women, who respond with "a joyful flutter." With part-of-speech tagging, we could zoom in on how the story's syntactical elements (especially verbs and adjectives) create this parallel between social and animal rituals.

    2. And now the landing-stage came out to meet them. Slowly it swam towards the Picton boat,

      This excerpt personifies the "landing-stage" with the verbs "came" and "swam." Where else does this occur in this story? And what does this device imply about the "voyage" that the story recounts? Part-of-speech tagging would allow us to examine when, how, and to what effect(s) objects becoming (grammatical) subjects through personification.

    3. And after all the weather was ideal.

      The story begins with the additive conjunction "and," which already suggests accumulation (and perhaps even festive excess) on a syntactical level. Some part-of-speech tagging and n-grams would allow us to see how often the speaker uses additive conjunctions, and to what effects.

    1. pervasively hostile environment. But merely offensive or bigoted speech does not rise to that level

      uh, yes it does for the person who the hate speech is directed against.

  15. course-computational-literary-analysis.netlify.com course-computational-literary-analysis.netlify.com
    1. My diary informs me

      This is an interesting reversal of typical subject-object relations. The diary, which is an object, is grammatically positioned as an informative agent, while Miss Clack, a person, becomes an object that is acted upon. Some part-of-speech tagging in scenes that feature document evidence would help us to better understand when and why this happens, and why it might be significant.

  16. Apr 2018
  17. Mar 2018
    1. Last month at Portland State University, when biologist Heather Heying made the point that women and men are biologically different, protesters in the audience screamed and excoriated her and tried to damage the sound system before they were removed. “We should not listen to fascism. Nazis are not welcome in civil society,” a protester scowled.

      The belief that sexism is at the root of fascism, although well founded, causes hyperactivists to censor scientists.

  18. Feb 2018
    1. “These are unprecedented, brazen acts of censorship by a corporate monopoly that controls a primary channel of public communication,” said Nehlen, who’s running against Ryan in the GOP congressional primaries in Wisconsin. “It has severely compromised the integrity of our election processes, and Congress needs to hold public hearings and conduct a full investigation into these matters without delay.”

      This language is ripe for studying.

    1. desde esta perspectiva las organizaciones constituyen conversaciones para la acción. Hay un cierto grado de recurrencia y formalización en estas conversaciones, que Winograd y Flores (1986) caracterizan en términos de actos lingüísticos distintivos. Las organizaciones son redes de compromisos que operan a través de actos lingüísticos, como las promesas y

      las peticiones. [...] En última instancia la característica central de las organizaciones y su diseño es el desarrollo de competencias comunicativas en un ámbito abierto para la interpretación, de manera que los compromisos sean transparentes

      [...] Una parte importante del marco de Winograd y Flores es el desarrollo de un enfoque lingüístico para el trabajo de las organizaciones sobre la base de ‘directivas’ (pedidos, solicitudes, consultas y ofertas) y ‘comisiones’ (promesas, aceptaciones y rechazos). En la década de 1980 Flores desarrolló un software para organizaciones, llamado El coordinador, basado en la idea de que las organizaciones son redes de compromisos que operan en el lenguaje. Véanse Winograd y Flores (1986, capítulos 5 y 11) y Flores y Flores (2013). Su objetivo era “hacer las interacciones transparentes [...] en el dominio de las conversaciones para la acción”

      La interacción entre organizaciones institucionalizadas y conviviales está ocurriendo para casos del hacktivismo en términos de peticiones (derechos de petición, entradas al blog) y promesas (hackatones, respuestas, proyectos).

      Una de las preguntas actuales es cómo hacer que las dinámicas de gobernanza propias de las organizaciones conviviales puedan ser coherentes y escalables a nivel barrio o ciudad. Qué infraestructuras favorecerían dichas posibilidades de acuerdos transparentes en red.

      Interesante reencontrar el software de Windograd y Flores y revisar cómo se adecuan o no a sistemas como wikis y repositorios de código y cómo el diálogo entre ellos podría alentar estas ideas de software para acciones transparentes.

  19. Nov 2017
    1. Itisreallyimportanttoconsiderthemasspeechactsandaskwhatclaimstheybringintobeinginorbymakingdeclarationsaboutrights.ItiseasytodismissthesedeclarationsthattheInternethasoccasioned,buttheyalsobegexamination.Somedismissthemfortheirostensibleineffectiveness,butthisisunderstoodintermsofconstativeratherthanperformativeeffects.Thequestionwe’dratheraskiswhat,ifany,imaginaryandperformativeifnotlegalforcedotheyhave?

      Esto me recuerda la intensión de escribir manifiestos en mu ypocas JSL, a la que yo me opuse, quizás por su percibida inefectividad con respecto a actos más performativos y enactivos. Quiźas me faltó entenderlo en esos mismos términos en lugar de como actos púramente enunciativos.

    2. OneaspectofhackerculturethatColemanhighlightsistheslogan‘codeisspeech’.[46]CodeisindeedthelanguageoftheInternet.Butisitspeech?FollowingAustin,wearguethatthroughspeechactswedosomethinginorbysayingsomething.Similarly,wewouldarguethatprogrammersaredoingsomethinginorbycodingsomething.Yet,toarticulatethismoreprecisely,codeisnotspeech:itisalanguageinorbywhichspeechactsareperformed.Justasinhumanlanguages,thedecisivethingsherearenotonlythelinguisticconventionsthatanimatespeechactsbutalsothesocialconventionsthattheybringabout

    Tags

    Annotators

    1. “free” as in “free and unfettered markets”
    2. Everyone has a right to free speech, but in practice many individuals have very little access to free speech. When we try to address this on platforms, by clamping down on things like harassment or bots, it’s portrayed as “curtailing” free speech, in the same way that making the rich pay more tax or follow regulations is seen by conservatives as “curtailing” economic opportunity.

  20. Oct 2017
    1. Tounderstanddigitalactswehavetounderstandspeechactsorspeechthatacts.Thespeechthatactsmeansnotonlythatinorbysayingsomethingwearedoingsomethingbutalsothatinorbydoingsomethingwearesayingsomething.ItisinthissensethatwehaveargueddigitalactsaredifferentfromspeechactsonlyinsofarastheconventionstheyrepeatanditerateandconventionsthattheyresignifyareconventionsthataremadepossiblethroughtheInternet.Ultimately,digitalactsresignifyquestionsofanonymity,extensity,traceability,andvelocityinpoliticalways.
    2. Theimportantthingistoseparateacts(locutionary,illocutionary

      The important thing is to separate acts (locutionary, illocutionary, perlocutionary), forces (legal, performative, imaginary), conventions, actions, bodies, and spaces that their relations produce.

    3. Itiswellnighimpossibletomakedigitalutteranceswithoutatrace;onthecontrary,oftentheforceofadigitalspeechactdrawsitsstrengthfromthetracesthatitleaves.Aswesaidinchapter2,eachofthesequestionsraisedbydigitalactscanarguablybefoundinothertechnologiesofspeechacts—thetelegraph,megaphone,radio,andtelephonecometomindimmediately.Butitiswhentakentogetherthatwethinkdigitalactsresignifythesequestionsandcombinetomakethemdistinctfromspeechacts,intermsofboththeconventionsbywhichtheybecomepossibleandtheeffectsthattheyproduce.
    4. ‘codeistheonlylanguagethatisexecutable.’[49]‘So[forGalloway]codeisthefirstlanguagethatactuallydoeswhatitsays—itisamachineforconvertingmeaningintoaction.’[50]WithAustin(andWittgenstein),thisconclusioncomesasamajorsurprisetous.Aswehavearguedinthischapter,forAustin(andWittgenstein)languageisanactivity,andinorbysayingsomethinginlanguagewedosomethingwithit—weact.Toputitdifferently,languageisexecutable.[51]Thereisnouniquenesstocodeinthatregard,althoughwhilecodeislikelanguage,itisdifferent.WethinkthatdifferenceistobesoughtinitseffectsandtheconventionsitcreatesthroughtheInternetratherthaninitsostensibleuniquenature

      El lenguaje es ejecutable!

    5. ThepremiseofthisbookisthatthecitizensubjectactingthroughtheInternetisthedigitalcitizenandthatthisisanewsubjectofpoliticswhoalsoactsthroughnewconventionsthatnotonlyinvolvedoingthingswithwordsbutdoingwordswiththings.
    6. Thekeyissueinspeechactsbecomeswhether,andifsotowhatextent,whatissayableanddoablefollowsorexceedssocialconventionsthatgovernasituation.
    7. Byadvancingtheideathatspeechisnotonlyadescription(constative)butalsoanact(performative),Austinushersinaradicallydifferentwayofthinkingaboutnotonlyspeakingandwritingbutalsodoingthingsinorbyspeakingandwriting.
    8. butbodiesandtheirmovementsareimplicitinspeechthatacts.
    9. Toputitdifferently,Austin’sconcernwithinfelicitousisnotaregretonhispartbutarecognitionthatspeechdoesnotonlyact,italsocanfailtoactorfailtoactinwaysanticipated.
    10. Bysayingsomething,Ihaveaccomplishedsomething.Thus,‘of’sayingsomethinghasmeaning(locutionaryacts),whereas‘in’or‘by’sayingsomethinghasforce(illocutionaryandperlocutionaryacts).
    1. The abuse is the free speech issue. Kicking Nazis off of Twitter reduces the platform of a small number of people who are using that platform to terrify and silence others. Leaving them on suppresses, in all meaningful terms, the voices of entire classes of female intellectuals, people of color, and any other subgroup the mob decides to turn it spotlight towards when that subgroup gets a little too uppity.

  21. Aug 2017
    1. The request from the DOJ demands that DreamHost hand over 1.3 million visitor IP addresses — in addition to contact information, email content, and photos of thousands of people — in an effort to determine who simply visited the website. (Our customer has also been notified of the pending warrant on the account.)

      That information could be used to identify any individuals who used this site to exercise and express political speech protected under the Constitution’s First Amendment. That should be enough to set alarm bells off in anyone’s mind.

  22. Jul 2017
  23. Jun 2017
    1. CINNA. I am not Cinna the conspirator. FOURTH CITIZEN. It is no matter, his name’s Cinna; pluck but his name out of his heart, and turn him going.

      In this act, mistaken identity is used to break tension. Apart from the obvious comedic relief this scene adds to the ever mounting tension and drama in the play, this scene also indicates the disintegration of society and the lack of social restraints of the general public after Caesar’s death.

      In this scene, the plebeians initially surround Cinna the poet after confusing him with Cinna the conspirator. Even when Cinna repeatedly tells them “I am not Cinna the conspirator”, the citizens, in their bloodthirsty rampage, still decide to kill him, stating that “It is no matter, his name’s Cinna”. This degradation of social standards and the crumbling of the social foundations of Ancient Rome bolster the image of the plebeians as ‘sheep’ to be swayed and controlled by the ruling classes, and solidifies their position in the play.

      It is also no coincidence that Shakespeare made Cinna a poet. In the citizens’ interrogation of Cinna, Cinna not only speaks for himself, but as a poet and as a projection of those in scholarly fields and free speech as a whole. With this, Shakespeare compels the audience to question whom poets and those who provide information to the public are accountable to, and whether free speech is more important than a stable and safe society.

  24. May 2017
    1. The FCC is investigating Stephen Colbert for a line he delivered during his monologue, addressing Donald Trump: "The only thing your mouth is good at is being Vladimir Putin's c--k holster."

      https://www.youtube.com/watch?v=HaHwlSTqA7s

  25. Mar 2017
    1. Rather than lend legitimacy to this event, we respectfully request you stand up for a campus that is intellectually open and culturally diverse, but one that does not fall prey to the designs of external organizations who peddle partisan propaganda in the guise of “public scholarship.”
  26. Feb 2017
    1. the grace and force of those ex-pressions which they used, when they sought to persuade or to affect.

      This thought reminded me of the discussion in class about how even babies are communicating before developing a sense of language.

      It seems to me that as long as an individual has an understanding of their own cultural ideas and contexts, they can grasp some form of rhetorical interaction with others; rhetoric seemingly always finds a way.

  27. Jan 2017
    1. anyone

      Insert "if" here?

    2. No, no, no, no, no.

      Didn't watch live, but assuming there was a negative crowd reaction here to mention of the pending inauguration...

    3. For every two steps forward, it often feels we take one step back.

      Foreshadowing? Is Obama calling out Trump as a one term president?!

    4. It’s why GIs gave their lives at Omaha Beach and Iwo Jima; Iraq and Afghanistan — and why men and women from Selma to Stonewall were prepared to give theirs as well.

      An interesting an powerful alignment of American military campaigns and the civil rights movement.

  28. Jul 2016
    1. “the free software movement does this.” And again, I have to say: not quite. 

      True. But some of us are saying something slightly different. The free software movement shares some of those principles and those go back to a rather specific idea about personal/individual agency.

  29. Apr 2016
  30. Sep 2014
    1. Amicus brief in Anthony Douglas Elonis v. United States, including a long section describing the origins and history of hip hop, calling for the court to take serious caution when ruling on the actual or real intent to harm communicated (or not) by potentially hyperbolic lyrics and braggadocio.

    2. What level of knowledge of rap and understanding of its complicated conventions is a defendant-speaker to assume, in advance of communication, that a hypothetically reasonable person possesses in order to properly understand a rap message? Because the answer is anything but clear and because a speaker’s First Amendment rights should not hang on what amounts to guesswork about an audience’s hypothetically reasonable knowledge of a complex artistic and political genre of expression, the actual subjective intent of the defendant-speaker must be considered in both the First Amendment and statutory true threats analyses.
  31. Oct 2013
    1. And, therefore, as infants cannot learn to speak except by learning words and phrases from those who do speak, why should not men become eloquent without being taught any art of speech, simply by reading and learning the speeches of eloquent men, and by imitating them as far as they can?

      Rhetoric compared to speech. interesting comparison, makes it closely linked to day to day activity

    1. The teacher will he cautious, likewise, that concluding syllables be not lost; that his pupil's speech be all of a similar character; that whenever he has to raise his voice, the effort may be that of his lungs, and not of his head; and that his gesture may be suited to his voice, and his looks to his gesture. 9

      Speech therapy?

    1. As there are two kinds of speech, therefore, the continuous, which is called oratory, and the concise, which is termed logic (which Zeno thought so nearly connected that he compared the one to an open hand and the other to a clenched fist), if the art of disputation be a virtue, there will be no doubt of the virtue of that which is of so much more noble and expansive a nature.

      Two kinds of speech.

    1. Before all things, let the talk of the child's nurses not be ungrammatical.

      the speech in the home greatly influences a child's ability to learn throughout life.

    1. In sounds also occur those faults of utterance and pronunciation, of which specimens cannot be given in writing;

      Speech is a different medium than writing and it is easier to detect differences in voice. We can choose to alter our voice, accent, and tone, or use these to our advantage

    1. A third would be the proper method of delivery; this is a thing that affects the success of a speech greatly; but hitherto the subject has been neglected. Indeed, it was long before it found a way into the arts of tragic drama and epic recitation: at first poets acted their tragedies themselves. It is plain that delivery has just as much to do with oratory as with poetry

      Comparing speech with poetry: both concerned with delivery (style)

    2. three things -- volume of sound, modulation of pitch, and rhythm

      Three stlyistic elements to be conscious of in speech

    3. In making a speech one must study three points: first, the means of producing persuasion; second, the style, or language, to be used; third, the proper arrangement of the various parts of the speech.

      Three areas of study (speech)

    1. For of the three elements in speech-making -- speaker, subject, and person addressed -- it is the last one, the hearer, that determines the speech's end and object.

      So this person determines whether the speech was a success or not? This sounds like an election speech, the end goal is to get the listeners to agree with the politician and vote them into office.