{"@context":"http://iiif.io/api/presentation/3/context.json","id":"https://amiastreaming.aviaryplatform.com/iiif/2r3nv9990b/manifest","type":"Manifest","label":{"en":["Reconsidering the Hermeneutics of Listening with High Performance Sound Technologies for Access and Scholarship (HiPSTAS)"]},"logo":"https://d9jk7wjtjpu5g.cloudfront.net/organizations/logo_images/000/000/016/original/AMIA-Logo-17.jpg?1556650205","metadata":[{"label":{"en":["Type"]},"value":{"en":["Presentation"]}},{"label":{"en":["Coverage"]},"value":{"en":["Museum of Modern Art (Place of Recording)","New York, NY (USA) (Place of Recording)"]}},{"label":{"en":["Date"]},"value":{"en":["2015-05-08 (created)"]}},{"label":{"en":["Agent"]},"value":{"en":["Tanya Clement (Speaker)","Chris Lacinak (Programmer)"]}},{"label":{"en":["Publisher"]},"value":{"en":["Association of Moving Image Archivists"]}},{"label":{"en":["Description"]},"value":{"en":["\u003cp\u003eFor over a decade organizations with legacy audio holdings have placed their resources and focus on digitization. Despite the fact that hundreds of thousands of hours have been digitized, searching through audio content has been constrained largely to text-based description, greatly restricting discovery. To address this reality, the High Performance Sound Technologies for Analysis and Scholarship (HiPSTAS) project is working on applying advanced computational techniques, such as spectral analysis and machine learning, to expand opportunities for discovery and research insights across audio collections. The presentation explores first results of the HiPSTAS project when applied to two bodies of materials. The first is the University of Texas Folklore Center Archives, containing collections from John and Alan Lomax, in which HiPSTAS enables discovery based on genre. The second is PennSound, containing poetry read by Allen Ginsberg, Robert Creeley, Cecilia Vicuña, and many others, in which HiPSTAS enables discovery based on dates, speaker, and venue. Tanya Clement is an Assistant Professor in the School of Information at the University of Texas at Austin. Presented at DAS: New York on May 8, 2015.\u003c/p\u003e (general)"]}},{"label":{"en":["Language"]},"value":{"en":["English (Primary)"]}}],"summary":{"en":["\u003cp\u003eFor over a decade organizations with legacy audio holdings have placed their resources and focus on digitization. Despite the fact that hundreds of thousands of hours have been digitized, searching through audio content has been constrained largely to text-based description, greatly restricting discovery. To address this reality, the High Performance Sound Technologies for Analysis and Scholarship (HiPSTAS) project is working on applying advanced computational techniques, such as spectral analysis and machine learning, to expand opportunities for discovery and research insights across audio collections. The presentation explores first results of the HiPSTAS project when applied to two bodies of materials. The first is the University of Texas Folklore Center Archives, containing collections from John and Alan Lomax, in which HiPSTAS enables discovery based on genre. The second is PennSound, containing poetry read by Allen Ginsberg, Robert Creeley, Cecilia Vicu\u0026ntilde;a, and many others, in which HiPSTAS enables discovery based on dates, speaker, and venue. Tanya Clement is an Assistant Professor in the School of Information at the University of Texas at Austin. Presented at DAS: New York on May 8, 2015.\u003c/p\u003e"]},"provider":[{"id":"https://amiastreaming.aviaryplatform.com/aboutus","type":"Agent","label":{"en":["AMIAstreaming"]},"homepage":[{"id":"https://amiastreaming.aviaryplatform.com/","type":"Text","label":{"en":["AMIAstreaming"]},"format":"text/html"}],"logo":[{"id":"https://d9jk7wjtjpu5g.cloudfront.net/organizations/logo_images/000/000/016/original/AMIA-Logo-17.jpg?1556650205","type":"Image"}]}],"thumbnail":[{"id":"https://d9jk7wjtjpu5g.cloudfront.net/collection_resource_files/thumbnails/000/035/671/small/Screen_Shot_2019-04-30_at_3.58.20_PM.png?1556657967","type":"Image","format":"image/png"}],"items":[{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671","type":"Canvas","label":{"en":["Media File 1 of 1 - Tanya_Clement_Final.mp4"]},"duration":1171.135,"width":640,"height":360,"thumbnail":[{"id":"https://d9jk7wjtjpu5g.cloudfront.net/collection_resource_files/thumbnails/000/035/671/small/Screen_Shot_2019-04-30_at_3.58.20_PM.png?1556657967","type":"Image","format":"image/png"}],"items":[{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/content/1","type":"AnnotationPage","items":[{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/content/1/annotation/1","type":"Annotation","motivation":"painting","body":{"id":"https://aviary-p-amiastreaming.s3.wasabisys.com/collection_resource_files/resource_files/000/035/671/original/Tanya_Clement_Final.mp4?1556656149","type":"Video","format":"video/mp4","duration":1171.135,"width":640,"height":360},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671","metadata":[]}]}],"annotations":[{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642","type":"AnnotationPage","label":{"en":["English [Transcript]"]},"items":[{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/1","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"am I don't know that I've ever been part of a %HESITATION talk of people that are so different in background from the FBI to wrestling to whatnot %HESITATION sell %HESITATION I'm gonna talk a little bit about today today about this project %HESITATION I want to start with a background behind the project %HESITATION I come from literary study %HESITATION my PhD is actually an English literature I found myself in in high school primarily because in %HESITATION the humanities we are also becoming %HESITATION well acquainted with big data %HESITATION as our tax get digitized as so I started %HESITATION my study %HESITATION thinking about tax %HESITATION and that soon became thinking about sound %HESITATION and what it would mean if a you know we're getting pretty good at searching taxed in looking at taxed and categorizing taxed and %HESITATION teaching with taxed %HESITATION what about sound %HESITATION so driving research questions for me were really to think through what it means to study culture through sound recordings as you can see from the previous quote %HESITATION from Charles burn sting his one of the directors of Penn sound a really large archive of sound recording projects of poetry recordings at you know you're in a poacher classroom you're typically looking anthology or typically looking at a poem on the page what would it mean to study poetry if you could actually might pass around recordings in the classroom which you would think would be easier than it than it is to think about annotating a recording or think about a student pulling a recording a pardon writing a writing a paper about it it's not as simple as it sounds so some of the research behind this is to really think through what that means to %HESITATION teaching research with sound recordings as opposed to text %HESITATION what is the acoustic experience what what does it mean to talk about sound %HESITATION and what impact does certain kinds of %HESITATION ways of accessing sound what does that what impact does that have on how we study in and teach with sound ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=9.56,127.02"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/2","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"so my talk is basically divided into three parts %HESITATION they're not equal length %HESITATION ends the first interviews the project to you and then the second and the third parts are to look at a couple of case studies %HESITATION the project is called high performance sound technologies and access and scholarship hipsters is is an acronym that I thought was funny when I was alone in my office and I didn't really think I was gonna get funded %HESITATION Sir so now I I run around with this with this acronym which it there's nothing really actually all that hip about the project many mature I know what it means but maybe that is the definition of it I'm not sure %HESITATION so it's been funded twice very generously by the national endowment for the humanities the first round of funding was for an advance was for advanced topics in the humanities out of %HESITATION the office of digital humanities and the basic idea was to bring together some people to work with software %HESITATION who hadn't done that kind of thing before %HESITATION the seconds grant is out of preservation access to sort of %HESITATION to make the software usable I'm gonna show you a little bit about that but first %HESITATION the team is a useful to know about in terms of understanding what we're doing and why we started doing it %HESITATION my collaborators are all at the university of Illinois %HESITATION they are research programmers and research scientists and then you'll notice this this strange aberration the biologist at the bottom %HESITATION these offer was actually built by David Chang for David and strum David instrument an ornithologist and he would go out and he would %HESITATION he would record hundreds of thousands of hours of of of sound %HESITATION because he wanted to research bird calls and %HESITATION he asked David Chang who is a %HESITATION machine learning expert of big data experts %HESITATION but also a musician and a person who's has expertise and signal processing if you could build in some software to do machine learning on his sound collections the basic idea being that David instrument go he would do his recordings and he'd be looking for bird calls in the recordings and he didn't want to sit and listen to every single second of it because that's a lot of time he wanted to make ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=127.99,247.48"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/3","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"sheen to find the bird calls in all of these recordings %HESITATION so this the they really reductive you know explanation how machine learning works is David ends from would would %HESITATION signify or tag certain recordings of birds and then the software would go find more bird calls that were like the ones that David identified as seed examples ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=247.51,269.55"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/4","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"so I had the clever idea well why can't we do the same thing with %HESITATION archival recordings that humanists are interested in %HESITATION and maybe that would facilitate teaching was sound doing research was found in scholarship was found and and so that first grant was to bring together these researchers so Argus in human scholars %HESITATION and advanced graduate students in humanities information science and allow them to use David Ching's software on collections of interest to them %HESITATION some of collections that we ingested at the beginning warm pen sound they have about thirty thousand audio files %HESITATION folklore from the Dolph Briscoe center for American history at UT and we were also working with people who are interested in native American projects at the American philosophical society which is about fifty tribes in three thousand hours I'm sorry big data doesn't sound as big data is %HESITATION as the previous as the previous conversation but it is big data for humanness humanness are often working with one book %HESITATION one one percent one poet one one ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=270.43,330.12"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/5","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"one one one not many many %HESITATION %HESITATION other people that came as participants for coming from the library of Congress they're coming from story core they were coming from other collections their their sound collections everywhere I put this line up just as to demonstrate that there are small and large collections of these things all over the place %HESITATION end our primary goal was to create a research environment in which users could better access and analyze the spoken word %HESITATION in this required us to assess what scholars were already doing we sounded that was part of the %HESITATION the impetus of the first meeting %HESITATION but it's also to sort of figure out what what kind of technological infrastructure what we need if you have twenty humanness in a room and they want to search thirty thousand hours of of audio %HESITATION what what does that actually entail in terms of data processing ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=330.96,377.66"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/6","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"and then finally running some tests to see okay well what can we do this you know given that we have a better understanding of the kinds of questions that they want to ask in the kind of infrastructure that that's involved if we actually do this kind of thing to stuff come back that people are actually interested in ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=378.98,393.69"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/7","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"this is an example of a spectrogram %HESITATION so the arlis offer as I indicated with the example about the bird calls it's not about speech recognition weren't we're not doing that %HESITATION we're really interested in other aspects of of sonic meaning meaning making so tomber in tone and rhythm think of all the things that you would be interested in a poem that that makes meaning along side the words but isn't just the words %HESITATION so Arlo makes these kinds of specter Graham's %HESITATION and allows a user to come in and I'll say an example in a minute tag these up %HESITATION this is actually frequency on the Y. axis in time on the X. axis this is Gretchen start recording of Gertrude Stein saying some such thing you can see the three the three words %HESITATION the intensity is a black is the coolest in white is the %HESITATION most intense this is the other aspect of it so we actually have it %HESITATION that infrastructure aspect is we have it installed on the super computer cluster at the university of Texas right now %HESITATION in order to kind of do this kind of processing over thirty thousand files I had a collection and we ran one of our first collection our tests on was penned sound as I described %HESITATION ten sound has recordings all the way back to what me whip man up into the present day and are constantly adding files %HESITATION at present time as of March first there about thirty five thousand files we did use of deduplication some preprocessing that's the other thing that you don't hear about in data is how much cleaning up in pre processing has to happen in order to do anything with data %HESITATION and so what we ended up doing was collecting we want to look for applause and pen sound people clapping and we the the third bullet point up there is we took three second examples across about two thousand files and we collected two hundred and seventy four examples of applause and five hundred eighty two examples not apply so that we can ask the machine you find me those areas of applause versus the non applause and we ended up protecting about applying that and the machine's production on night team ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=394.98,514.5"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/8","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"a hundred and forty eight files because those duplications came back ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=514.53,517.86"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/9","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"someone to play a little exam before eve what it looks like to see %HESITATION some pause in pens in %HESITATION are low ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=519.08,524.96"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/10","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"it plays ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=526.3,526.78"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/11","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"this is the problem we thought we were going to have ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=532.9,534.77"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/12","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"do we figure out the movies won't play ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=543.7,545.38"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/13","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"okay no ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=546.76,547.46"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/14","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"all right we'll try it one more time and then we'll and then we'll just imagine ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=548.3,551.35"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/15","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"okay that's what applies sounds like so then here in being this is actually what applies looks like a human being comes and it was actually really clever little thing that the poet said so I was happy to entertain you but you seem to be entertained anyways %HESITATION ends so user comes and says okay I just want to take this little example here I'm going to drop box around this on the spectrogram here you go machine here is an example and then the machine comes back this example is over and green on the left and then it comes back with other examples think about you know years basically searching sound was sound and it comes back and says are these sounds like the sounds that you want that you're looking for ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=552.8,585.66"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/16","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"the data behind it ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=586.64,587.86"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/17","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"looks like ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=588.8,589.77"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/18","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"this %HESITATION and you pull out different kinds of data so what you see there is the file ID the next column is the times the first second and second and a half in two seconds in two and a half seconds etcetera and then the machine makes a prediction whether at that point in time applause is happening or is not happening %HESITATION and the number is the higher number is the higher predicted value that it is happening so if you visualize data like this what you get is %HESITATION on the Y. axis again you have the probability the machine thinks that there is a pause happening during this file and along the bottom you have time so the machine has said that you know look it looks like somebody's applauding at the end of this poetry performance %HESITATION we see that again and again in the collection %HESITATION sometimes you see people who get ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=590.68,635.18"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/19","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"a lot of applause for a long time and you say okay well why don't you know what why is this person getting so much applause %HESITATION and we made little multiples and you can see across the file now this is kind of nice if you're someone who's looking for applause right like this would be a nice search result to get %HESITATION or you might see some examples like these is a pleasant beginning at the end someone gets you know that the whole thing starts you applied and then you're part of the NCC a bunch of those ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=636.32,658.15"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/20","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"%HESITATION what's interesting though is when you start to see things like this and you start to question what's happening for the applause right %HESITATION and you might say if you're interested in %HESITATION whose introducing these people you might be interested in knowing where the applause starts and where it keeps going so we see a bunch of these examples ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=659.81,676.71"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/21","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"but to those %HESITATION for group readings at you can see applause's delimiter between people who are speaking and as a scholar you might like to know who gets more applause in reading you know that guy towards the ends not so much applause you know %HESITATION why ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=678.86,692.72"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/22","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"we see a bunch of those %HESITATION for single performances plies can show up as a dilemma between readers which columns get the most applies so this is one person reading a bunch of their palms who %HESITATION man that one time did not go off well ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=694.18,705.43"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/23","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"you know and that's interesting to a scholar because they might say okay well what poems in what venues are actually more %HESITATION you know drawing more response from the audience %HESITATION we also saw this interesting aberration where we saw applies happening about two thirds of the way through a single performance or a single person he was performing %HESITATION and we start to think well maybe there is this problem and they had this sort of day you want this this climax of poetic gesture and and the audience just stood up and you know applauded in the middle of this poem %HESITATION and that's really not what we saw %HESITATION what we did see was that there would be a pause before the end before questions but again for people who are studying these kind of performances that's interesting they want to know what kinds of questions are being elicited for certain kinds of audiences xterra ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=706.45,750.68"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/24","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"you see a bunch of those are their mistakes yes there are mistakes %HESITATION if it's strong hiss is there the machines are those replies %HESITATION dissonant music I thought that was a plus and %HESITATION the bagpipe that's definitely applies so %HESITATION all this is to say that these these these kinds of interventions are not perfect %HESITATION it takes a little you know thinking about well what what sound indicators are in there that might be of interest to people %HESITATION in using those to your advantage but this is it this is a view of a sound archive that we do not currently have ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=755.25,788.3"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/25","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"%HESITATION what other kinds of questions can you ask about you know you might be interested in gender which which gender who gets more applause if somebody's %HESITATION more advanced in their career do they get more or less supplies if they're sort of in the village verses at a university do they get more plus these are kinds of questions that are interesting these kinds of questions cannot happen though if if I met a data isn't a isn't a blob right %HESITATION so that was the other thing that we found is that even if we do a lot of this sound analysis %HESITATION if we don't have good meditated to orient you know %HESITATION as I showed you on the one side so I might be interested in in who's doing the introduction if we don't have the information about who's doing the introduction %HESITATION in in a way that is pulled out it's hard to kind of negotiate that data against that information as well so this is kind of an example of yucky metadata ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=789.55,834.49"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/26","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"that you would need to sort of pull out and all of these ways in order to make it meaningful these are publications that we did on this on this work on these are just a couple more examples I'm gonna spend through there all on jacket to which is a magazine associated with Penn sound encourage you to go there %HESITATION this particular person Christmas does it was also hipsters participant was interested in %HESITATION noises the content so he wanted to know the provenance of recordings and so we had some recordings that he knew the prominence of and he %HESITATION found since sort of sounds tags in there that would allow him to say were other recordings had been recorded %HESITATION this is Eric rapper he was interested in laughter %HESITATION in the extent to which when an audience laughs it has a it has a meaningful impact on what happens in poetry can sure would was interested in you know what if one poll and what what is one pull it actually comes and %HESITATION you know does does the same poet but very differently in different venues you know can we can we look at those kinds of differences %HESITATION even though the words are all the same the way they say the words will be different and then this is merit macarthur who is interested in %HESITATION the end contend the incantation of poetry performances and why they all talk like this ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=835.55,903.47"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/27","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"I another as sort of use case that we're interested in is %HESITATION ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=904.97,909.98"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/28","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"at folklore collection at the university of Texas %HESITATION the %HESITATION a what we did was we had about two hundred nineteen hours of recordings for her in fifty five files we tag about four thousand two second windows with %HESITATION instrument spoken in song these are field recordings ago for about nineteen twenty six to the sixties and imagine you know people going out into the field and they're recording people her singing they're getting tales from them %HESITATION sometimes people are seeing over an instrument sometimes people are singing a cappella and so we wanted to be able to kind of %HESITATION to map the terrain of these recordings such that you could see when these things were happening is wrong words changes were happening this is %HESITATION a a John Alan Lomax recordings is about fifty five of them in that collection from nineteen twenty six to nineteen forty one and again this is a %HESITATION it's kind of hard to see that this is a a display of the collection that you don't normally get right so the %HESITATION what you have here is the blue is someone singing %HESITATION the red is the machine predicting that there's an instrument happening and the green is is someone whose %HESITATION is if their speech and so when you see red and blue happening at the same time more than likely somebody singing with an instrument %HESITATION and what you see you know if you're an architecture scholar in your coming to this you might be particularly interested in this section and I squared here which seems to be someone playing an instrument and then they and then they start singing %HESITATION here's another sort of illustration of that %HESITATION dynamic the blue is is an instrument and the oranges someone speaking %HESITATION and you might care to know when you know if you're if you've got recordings of Bob Dylan you might like to know what Bob Dylan is saying in between his sets right %HESITATION and this is a view that you don't normally get of a collection ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=910.82,1016.28"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/29","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"what this is is %HESITATION it's across time it's the collection and what you have is %HESITATION the blue is the total number seconds of a recording %HESITATION they're going across time to the right the red is when someone is speaking the number second someone is speaking and the file the green is the number of seconds someone's playing an instrument and the purple is the number of seconds that someone is singing %HESITATION the little movie if it played would go across time and you would see what I was particularly interested in is is how much more time was spent on people who were speaking in the files because eyes field recorders %HESITATION John Lomax for example was going out into the field his primary interest primarily interested in collecting songs but was not too interested in speaking to the people he didn't really want to know their stories he wanted their songs this trend changes over time for a number of reasons %HESITATION it recording got cheaper at you know recording equipment got lighter %HESITATION reels got longer %HESITATION but what's interesting is even when the recordings across this view point change in time and more speaking happens the recordings don't seem to get longer so there's something else going on there there's an actual cultural impetus to collect more stories from people than just going and taking %HESITATION their songs and I'm using his words delivered deliberately %HESITATION but anyway the point is is this is an interesting you point into the sound recordings as data based on kinds of questions that would be interesting to scholars ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=1017.12,1101.54"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/30","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"I am writing I'm putting this out there because I'm writing a little bit on this on the sound studies blog so if you're into it %HESITATION sounding out so if you're interested in in hearing more about that particular thing and then you can go there %HESITATION because right time today but I I wanted to and sort of with that with the with the notes so when we're talking to scholars and we're talking to the arc of this what they're interested in in terms of sound dynamics for these collections was %HESITATION talking about temple were pitcher toner tomber dynamics %HESITATION laughter silence all of these things that indicates you know what people are doing and how people make meaning %HESITATION and how we make meaning with our cultural artifacts but if you're using a system like Arlo you also have to be adapted damping ratios and gain and frequencies inspector and energy and pitch energy and the kinds of questions that I'm asking are a release date is to figure out you know we're do those two things meet you know how do you work with scholars so that they can they can work with these kinds of of tools to figure out what the data means ","format":"text/plain"},"target":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671#t=1103.13,1157.72"},{"id":"https://amiastreaming.aviaryplatform.com/collections/48/collection_resources/4778/file/35671/transcript/3642/annotation/31","type":"Annotation","motivation":"transcribing","body":{"type":"TextualBody","value":"nothing thank you 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