Blog 2

My area of expertise would be jazz. One term that I always find people being confused of when used among my friends is the word "bad". When someone refers to someone else or what they are playing as "bad" it means they are killing and sound really great or really hip. This obviously can be confusing. Another word would be the "shed" or "shedding" which means the place where you practice or practing, someone might ask "what's up" and a response could be "hittin the shed" etc. Lastly the word "out", either as "that shit out" meaning the music or idea or the subject in general is very hip and modern, or a "that's out" as in not not really that killin (you will know that connotation when you hear it).

Lastly I think the most inaccurate conception of jazz is for it to be miscontrune as a "series of wrong notes". I feel this is disrespectful to the art that jazz is.

Benjamin Green

I work in computer science, machine learning (basically trying to glean actionable insights from recognizing patterns in data) to be specific. Some buzzwords are: -Scalable: This means the algorithm (theoretical description of the procedure) or implementation can run in a "reasonable" amount of time on very large datasets (millions of data points). This is very relative, but with the current trend in machine learning being to work on bigger and bigger data sets, many papers need to make the claim that the techniques they propose are scalable. -Fast: Broadly speaking, this means that the algorithm performs slightly better in theory than the next best algorithm known to solve the problem. It may still take a long time to run in practice. In particular, it doesn't refer to an absolute measure of time. -Data-driven: an adjective used to describe a choice made with machine learning techniques (based on a pattern in the data). Basically "we used machine learning." This sometimes is used in machine learning to make it clear that certain choices are made for principled reasons rather than dark art on the part of the researchers. But it's more often used by other fields who realize that machine learning and "data science" is hot right now and want to claim usage of it. All of this is a little tongue in cheek. I like my algorithms to be scalable, fast, and data driven too. These terms can be overused (especially in academic papers trying to get past conference reviewers) but machine learning does yield impressive results in many fields, even music and the arts. One term that gets used in a derogatory way in computer science in general is "hacky". This might refer to a piece of code that was made to work by trying unprincipled or sub-optimal techniques until something works, as opposed to being actually elegant or cleverly written. More importantly, many people refer to most of programming as "hacking" perhaps a bit unfairly. (Both within computer science, where theoretical computer scientists may look down on some efforts from the empirical community--this is true even at a more specific level in the machine learning community, and from non-computer scientists.) There is value in trying to insist on maximum elegance, since this corresponds with other people being able to read your work and use it themselves. However, I also think that "hacking" is important since no one starts off knowing everything, but it is a very valuable skill to get interesting things work by any means necessary. I think "hacky" should carry more of a connotation of "scrappy".

My area of expertise lies in music production and electronic composition. Three words that are often not universal are:

1. MIDI - (Musical Instrument Digital Interface) a language standard for interconnecting electronic musical instruments and computers. Basically this is an electronic instrument signal language that sends messages to and from each other and/or a computer. For example: if you plug a keyboard into your computer and play notes that you can manipulate on the computer, all that information is being send by MIDI.

 2. ADSR Envelope - (Attack, Decay, Sustain, Release) this is a term referring to the amplitude envelope used in some synthesizers. Attack - the time it takes for a sound to go from nothing to its loudest point. Decay - the time it takes for that initial attack to the sustain level. Sustain - the level at which the sound remains while holding the note. Release - the time it takes for the sound to fade to nothing once the note is no longer being played.

3. DAW - (Digital Audio Workstation) any electronic system designed to record, edit, and playback digital audio. Any music production software is a DAW. For example: Ableton Live, Logic, FL Studios, Cubase, Reason, Pro Tools, etc.

Something that is mentioned quite a bit when referring to my area of study, is a misunderstanding or limited view of what people like to call “real music.” Plenty of people will ask me “do you play or write any real music?” This is probably one of the most degrading things to me, especially because of the fact that I have been a percussionist for 11 years and not just “pushing buttons on a computer.” (another phrase that degrades the complexity of good music production). The way I view music is simple. It is an emotion and a feeling. No matter what kind of technologies, materials, or objects where used to make the music, as long as it invokes an emotion or feeling in you, it is real music. Period.

Blog 2

In each discipline, and really in any human endeavor that involves a closed group, the members develop an internal language that has specific meaning for them and little or no meaning for those outside the group. Even words that are in normal usage take on a new meaning in the in group. What are three of your favorite words from the 'secret language' of your discipline, and why are you drawn to them? Conversely, people outside of the group, not knowing the intricacies of the discipline, tend to reduce the function of the group using an unfair condensation of one or two words that they use to describe the totality of the group. What is the outsider description of your discipline that you find to be most inaccurate, reductionist or plain wrong? Due Sunday, 11:59 PM.

This is a piece I recorded with my quartet about a year ago, I hope you all enjoy! The piece is entitled Billies Bounce and was written by Charlie Parker.

https://www.youtube.com/watch?v=JU3yf3tu94A

This is something I'm interested and have always wanted to do. I think electrifying the trumpet and using effects is super super cool and I've always wanted to experiment with this aspect of the horn. I'm going to post two links, one is an example of an electrified trumpet and the other is a recording of Miles Davis's electric ensemble where he uses his trumpet with a violin pickup.

electric trumpet-  https://www.youtube.com/watch?v=7ER_RsaHCUc

Miles Davis-   https://www.youtube.com/watch?v=bxSFSdcGPLM

Here is an audio piece I made for class last year. It is composed entirely out of found sounds from my dorm room, around campus, etc. Everything I am currently working on is unfinished so I figured I would just post this.


The video below is obviously quite a large scale production, but I have always loved the way projection mapping and light were presented in this video. I hope to do something that is visually intriguing like this is, but also something a little more interactive, and of course with lots more music.

Here's an audio recording of a composition I made for erhu, a traditional Chinese instrument that could be compared to a violin (synthesized in Garageband--I only wish I could play one well enough to make decent music) accompanied by an acoustic hammered dulcimer playing and various electronic sounds and effects.  I chose this because it demonstrates some of my classical and folk influences as well as my interests in combining acoustic and electronic sounds and techniques (and how far I have to go as a composer and as a student of electronic music).

In the spirit of combining acoustic and electronic textures, one direction I'd like to go in would be to augment acoustic instrument performance (something I feel more comfortable with to date) with live electronics, as in this composition by Kaija Saariaho:


As I indicated above, I like acoustic music and think that it and electronic music have a lot to offer each other.  But in comparison to what I know how to do now, I would like to use electronics to enhance the performance, not just in playback.  I like the aesthetics of this piece (not that the recording is of the best quality) and some of her other work in a similar vein but for other instruments like the cello.