zygoth

My second song on the idiopan. I wanted to incorporate more percussive sounds, like you hear from handpan players. https://www.youtube.com/edit?o=U&video_id=ZYMAJtm2RWk

Hi all, I've started recording songs on my Idiopan and wanted to share this. If you have any feedback, please share!

Hi all, I'm pretty inexperienced with the whole recording thing and have a question for those who know more. I'm working on recording samples for a sampler I want to release for an instrument that doesn't have any yet. (it's an idiopan if you're wondering) I went and recorded a few samples at a local recording studio and I'm wondering if their quality is good enough. I'm worried that there's too much ambient noise in the audio. I'm posting a link to a few examples of probably the best quality I'm going to get at that studio--can anybody tell me if these samples are good enough or if I need to go somewhere more soundproof? Thanks! https://drive.google.com/file/d/0B6V741rUzUuvN20tQUlLdDdpMm8/view?usp=sharing https://drive.google.com/file/d/0B6V741rUzUuvZ0F1aXBfdHY2TUU/view?usp=sharing https://drive.google.com/file/d/0B6V741rUzUuvYjJPSUtXRVN1S2c/view?usp=sharing

Hey all, just wanted to let you know what happened with this. I ended up doing both recommenders, one based on DSP and one on tags. You can read my final report and see all the recommendations here: https://drive.google.com/folderview?id=0B6V741rUzUuvVkFMUXZoY19qTm8&usp=sharing Let me know if you have any comments or questions, hope you enjoy!

Cool. Do you have any idea yet of how long it's going to take?

It says re-tagged albums, not songs. Am I misunderstanding it...? As far as the songs go, wouldn't it be easiest to just open it up and let the whole community do the tagging?

Hey everybody, just wanted to update you on how the project is going. I have a basic recommendation system working now, which rates songs' similarity by how many tags they have in common. I've put the code on github, mostly just so you can look through the recommendation files if you're interested. Here is some sample output (first the similar song, then the tags they have in common). For the song "A Different Kind of Peace": Then the Healing Came orchestral,strings,cinematic Shield of Legend orchestral,epic,cinematic Justice for All orchestral,epic,cinematic Captain of the Skies orchestral,epic,strings,cinematic Enemy Underworld orchestral,epic,strings,cinematic For the song "Adlehyde Castle Flow": Insecta Robotica mellow,jazz,electric-piano This Heart percussion,mellow,tempo-slow Gemini Salsa percussion,jazz,tempo-slow Holiday Frappe mellow,jazz,electric-piano Fighting (7/8 Jazz Spiritual) mellow,jazz,electric-piano There is still a real sparsity of tags--only 1,306 songs even have one tag, and only about half of those have more than one. My next move is to incorporate Remixer and source-game as tags, by extracting the meta-data from the MP3s. That should help, but it seems like to be successful the tag-based system needs more data. Once again, does anybody know how to see a list of all the tags in the system, not just that page with the top 70? EDIT: forgot the github link... https://github.com/zygoth/OCR-Music-Recommendation-System/tree/master/

So I've finished creating a file with a list of all the songs and their corresponding tags. I have a few questions: What do these tags mean: compo, compo-dod Should I ignore these tags as irrelevant: resub, collab What regex would you recommend I use to extract the title only from a string like this: Majora's Mask 'Serious Moon Business' ? My simple regex '.*' gets: 's Mask 'Serious Moon Business' because of the extra apostrophe in the game's title. Where can I see a list of all the tags, not just the top 70? Other notes: There are currently about 5,000 tag-song pairs when extracting the top 70 tags. Almost all of them are for OCR1000-3000 and not any of the earlier songs. I haven't looked at the distribution, but on average we're talking 2-3 tags per tagged song, and 1000 songs with no tag info at all. This seems a little sparse to make a good recommender, but maybe when I add in all the tags that aren't in the top 70 it will get better. At any rate, I can make a system that will update automatically (barring any major site overhauls) so that as tags accumulate over time the recommender will use the new data. After thinking about the project a bit more, I think the recommender might work best as a sort of Amazon-style "Items Bought Together" section on song pages. On each page there would be a "Similar Songs" section with the 5 songs that share the most tags with the song on the page. This would obviously require djpretzel(or whoever he has delegated to run the site)'s permission. I have no idea how likely he would be to give it.

Is there any easy way to extract the tags for each song in the database? I didn't know what I was looking at when I first looked at the tag page. o.O It looks like there is a lot of information there, I would be willing to try tags if I can figure how to get all the data. I hadn't thought about the problem the torrents would present, I guess I just assumed most people downloaded songs one at a time to their library like me. I may have to use a more subjective method of validating my program, like surveys/feedback from the OCR community.

How complete is the tagging database? If it was mostly complete I would consider using it instead of DSP. I appreciate your comments about the possibility of my project. I feel I'm trying to solve an easier problem even than 4-genre classification though, because I'm not trying to classify songs by genre, only find pairs of songs with similar features. The final output of my audio analysis would be a list of pairs of similar songs, which the recommender would use to find songs that are similar to songs a user has already downloaded.

I'm not familiar with OCR's tagging system, could you explain more? When I look at my mp3s, all I see is things like Composer and Remixer, which are not really relevant to my approach. Also, some papers that I have read have led me to believe classification via DSP is possible with at least moderate success: http://ismir2001.ismir.net/pdf/tzanetakis.pdf http://www.cs.cmu.edu/~yh/files/GCfA.pdf I plan on using JAudio for feature extraction and WEKA for clustering.

Yes, that sounds great. The only thing I would add is a -1 option to the ls command so that I get one filename per line. Also, you could even do *OC_ReMix.mp3 so even if other types of songs are mixed in you only get the OCR ones. So, the commands would look like this: dir /S /B *OC_ReMix.mp3 > ocrlist.txt (Windows) ls -R -1 *OC_ReMix.mp3 > ocrlist.txt (Linux/Mac) All of the songs are titled this way, right?

Hm, I understand your concerns. All I need are the filenames, so as long as those haven't been changed I could probably just do it with a 1-liner batch file. That way everybody can see what they're running.

Hi all, I am a computer science major and am currently in a Big Data class where we do our own project. I am planning on creating a music recommendation system specific to OCR, by using some audio analysis tools and then clustering similar songs together. In order to test the effectiveness of my approach, I need the personal libraries of some actual OCR listeners. My plan is to make a simple program that writes the filenames of all files in a directory to a text file. Volunteers would copy this file to the directory with their OCR music, run the program, and email me the text file. If you are interested in volunteering your music library, please post on the thread. I will have the programs done within the week, and I will post links to them there. Let me know if you have any questions. Thanks! Zygo