Today Nicole and I made a quick little video on how to make a random note generator in Max MSP. It’s a little lame, but it’s a video!
I am actually super familiar with Camtasia, as I spent a year in my previous job designing, recording, and posting tutorials for the software that the company sold. I added music, voice overs, and effects to teach all levels of users to work in a fairly complicated program. Due to this experience, I can certainly see how it would be useful in an online teaching context. Unfortunately, I had some trouble getting the sample videos to play, but I am interested in seeing the various types of educational videos and how they can be used in the humanities. I have documentary style videos in mind, but surely there are other, more interesting ways to present streaming information. Particularly in music – we might be able to do live score analyses that that student can follow and replay, or combinations of photos and text for online classes.
In any event, I’m interested in getting these videos to work, so I will comment on those once I get these figured out.
Before this assignment, students will have already read chapters 1-5 and 8 in Electronic and Experimental Music by Thom Holmes. These chapters outline the history of electronic and digital sound, as well as what tools were available to artists during certain parts of the 20th century.
- Read through “Midi Basics” tutorials in the Max reference materials.
- Build a random note generator in Max MSP.
- Note generator should be able to 1) Start and stop upon command, 2) Play random notes continuously. Tempo of the notes should be variable. 3) MIDI code for the notes should be variable. 4) Entire patch should be commented out in detail.
- I will assign each student an algorithmic music piece by various composers (Laurie Spiegel, Milton Babbitt, Ianis Xannakis, Stockhausen, etc.)
- Have each student write a short essay (2 pages) answering these questions: 1) How does this composer use algorithms in this piece? 2) Why does this composer use algorithms to make music? 3) How to digital tools allow the composer to create express themselves in unique and interesting ways? 4) How does the historical moment in which this piece was composed impact the timbres, rhythms, and textures available to the composer?
I’m genuinely excited for this week’s material because it touches on huge issues of digitalization of “objects,” which I deal with in one of my favorite papers that I’ve worked on. I deal with the removal of ephemera from intended spaces, but mostly in the context of sound/performance art pieces. In the conversation around the 3D printing of the Palmyra arch, Sarah Bond touch on similar issues of space and experience, but with the added complications of humanitarian concerns and colonialism. I’d love to know more about the motivations behind the project and why they chose New York as a temporary home for the exhibit.
The 3D renderings, however, seem like they would be an amazing teaching tool. When I opened the model of the Rosetta Stone, I actually got goosebumps. There’s something about being about being able to manipulate and zoom into the text that is particularly compelling. I can absolutely see how using these models could be useful in a classroom. Something that was particularly cool is that there is a renaissance era viol de gamba with notations in the collection. I could absolutely see myself using that in a classroom, particularly in a smaller school in which there may not be a viol available in instrument storage.
First round effort:
Here’s a better one:
- Tool for plotting large numbers of pictures, compatible with jpeg, tiff, etc.
- Super useful for game, video, social media or art analysis
- I wonder if this could be used for scores? Album covers? Musicians’ marketing materials. This tool is really neat and I’m trying to think of ways in which it could be used in musicology. Obviously most of what I do pertains to sound, but there are surely ways in which I could work in imagery and image analysis.
- Surprise Lev Manovich! It looks like he’s working a lot on identity and social media right now (not surprising), but it’s needs to see some of his current output.
I might actually steal this article for when I teach digital audio courses in the future. This is one of the better break downs of connector types and recorder settings that I have run across. Albeit, there are sections that betray that it was written six years ago, such as the mention of CDs (which no one uses anymore) and the dominance of 16-bit recording. I will say that the section about file formats is also a little misleading in that it implies that .WAV files are not as universal as MP3, when in fact .WAV and .MP3 are the only two largely universal file types. Wave files are also becoming easier and easier to transport, upload, and use in streaming settings due to the leaps and bounds made in memory and storage in the past 5 years.
These posts are… a little all over the place. I feel like they are actually more valuable for learning about archival best practice and standards/trends apparent in the historical documentation field. Just skimming through them, it’s easy to glean ways in which an amateur or student might replicate their professional archival techniques. However, the technical aspects of these posts are far from useful. For example, the “Stitching” post is a long and rambling explanation how to merge videos without data loss. Really, that’s something a quick google in ProTools tutorials should be able to teach pretty quickly, and without the pretentious tech-speak introduction. Similarly, the “Stripping Audio” post has a great explanation as to why it might be better to send audio to transcriptionists (although I’m not sure how uploading and sending a Youtube video is cumbersome), but then just gives a few bullet points on how to strip audio in VLC, Quicktime, and ProTools. Does there really need to be a post for that? Any enterprising software user is just going to google search how to do it, why waste the reader’s time with pedantic click-paths?
Conclusion: interesting information about archival best practices, wastes a lot of time with arcane information about software use.
While mapping is not particularly interesting to me, the Richmond Emancipation project was very addictive and fun to click through. This mapping project is a great example of creative and effective presentation of information, but I’m left to wonder what questions or arguments can be gleaned from this map? Is it for student exploration or can it be used to support a complex argument? What purpose does a presentation like this do that a collection of these archival records with regional titles does not? This is a recurring and elusive question that keeps coming up as I explore different projects. Visualizations are compelling, but are they really effective at assisting historical interpretation?
The one platform that was interesting in the “Basics of Mapping” reading was “Hyper Cities.” Though it appears it would be most useful as a teaching tool, Hyper Cities appears to be robust enough to provide a distinct sense of place, space, and atmosphere in animating the history of a certain person, city, or event.
As a musicologist, I’m left to wonder how mapping could even be applied in my field. The first thing that comes to mind (although not my area of research), is using letters and performance reviews to track the travels of cosmopolitan composers like Handel. Many of the common practice composers were bound to a noble or royal families and their travels were dictation by those of their patrons, so that mapping project may not be so informative. Mapping the travels of famous divas or castrati of the 18th century, however, may provide an interesting look into taste, urban areas, and operatic trends.
The material for this week is particularly exciting for me, because the examples are the type of network diagram I would like to do for my project. In particular, the interactive diagram of the Plantagenet family is both a network diagram and a timeline, which is almost exactly what I had in mind.
I have collected roughly 25 forum threads, Reddit threads, and blog posts with comments sections relating to the issue of low numbers of women in high end audio. These posts have any where from 5- 200 users comments in them that represent various stances on women in and outside of the community. These posts usually fall into one of four (ish) categories:
1) those who think women are biologically/essentially un-inclined to pursue high end audio as a hobby (men are from Mars, women are from Venus fallacy)
2) women are unable/unwilling to engage with any technology, including high end equipment
3) the problem is not women, it’s the largely male and misogynist community/cultural constructions preventing women from entering DIY hobbies
4) the user is a woman in the community (this is the least common type of post)
Between 2011 and 2014 (particularly in December of 2014), there was a great deal of online hand-wringing over the issue of gender in the community, and as such, there were many blog posts and forum discussion on the topic. Many of the authors of these posts refer to other bloggers who had written on the topic as well as link outs to other similar posts.
I would like to take all of these posts and create a network diagram of users’ stances, types of posts, and references to one another on a timeline. Since all of the posts are time-stamped, the dates will be among the easiest information to collect. From there, I would like nodes to represent each post/author with a unique color to represent with category of response that that post falls into. Each comment will be connected to it’s parent blog or forum site, and posts that refer to one another will be linked in the network. Through this diagram, I hope to visualize the leanings of certain forums, blogs, and comments sections to better understand the distribution of opinions across the high end audio community.
As far as data collection goes, the blog posts are not too difficult because their comments sections are relatively small. These are not particularly cumbersome and can be done by hand. The forums, however, have hundreds of posts, so I am still considering how to collected and categorize each user and their opinions.
We created a comparison of Obama and Trump’s State of the Union speeches and found some interesting word use comparisons. Obama appears to use the term “know” more often than Trump, and has a more even vocabulary distribution across the whole speech than Trump. Trump tends to use similar words in high concentration in small sections as he moves through the speech. It is also interesting to note that Trump name drops enemy forces, such as ISIS and North Korea in a good chunk of the end of the speech. Both Trump and Obama use “America(n)(s)” a significant number of times, as well as “taxes,” although Trump does say “taxes” almost twice as much as Obama.
This coursebook actually surprised me. Given the terrible user interface, I was concerned that this was going to be either wildly disorganized and full of irrelevant content. However, upon looking further into the content, this may be one of the favorite things we’ve read this semester. The tools introduced, particularly Voyant-Tools seems really useful for what I’m doing. The explanations of issues of interpreting text in digital humanities, particularly the problems inherent in the interpretation of data.
The tools introduced in this text, like MALLET and Paper Machines seem super useful. I think the data cleaning/training information in the first article is way more thorough and useful, though.
This article points out some important intricacies of the problems in interpreting textual data. As Brett says, STEM students have way more experience in understanding problematic data, but I feel that a little bit of logical thinking should be enough to help a person legit results.
Really great examples of not only how to use MALLET, but also how to interpret data. Lots of different types of graphs.