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AcousticBrainz
labs.acousticbrainz.org
Cross-collection evaluation for music classification tasks (ISMIR 2016)
http://labs.acousticbrainz.org/ismir2016
Cross-collection evaluation for music classification tasks (ISMIR 2016). Aug 8, 2016. In the The 17th International Society for Music Information Retrieval Conference (ISMIR 2016). Conference we proposed a method of evaluating the accuracy of a classification model by comparing it to a separately created dataset. Read the paper. The code which we developed to perform this analysis will be available at https:/ github.com/MTG/acousticbrainz-labs/tree/master/cross-eval.
Last.fm genre annotations
http://labs.acousticbrainz.org/lastfm-genre-annotations
Aug 8, 2016. We have prepared a number of genre datasets in the context of our research presented on the 17th International Society for Music Information Retrieval Conference (ISMIR’16) and the 3rd International Digital Libraries for Musicology workshop (DLfM’16). These datasets include genre annotations inferred from Last.fm folksonomy tags found for many recordings in AcousticBrainz. For our ISMIR’16 paper. We used a genre tree. Discogs, AllMusis and Itunes genre trees. For our DL4M’16 paper. We decide...
Million Song Dataset Echo Nest mapping archive
http://labs.acousticbrainz.org/million-song-dataset-echonest-archive
Million Song Dataset Echo Nest mapping archive. Jul 1, 2016. The Million Song Dataset. Was released in collaboration with The Echo Nest. And uses Echo Nest identifiers to refer to each track. While the metadata that comes with the dataset includes names of tracks and artists, in June 2016, the Echo Nest shut down their API, leaving no service available which understood the IDs. Endpoint for each Song ID. The queries included the following rosetta stone buckets:. We provide the following file. The archive...
Million Song Dataset to AcousticBrainz mapping
http://labs.acousticbrainz.org/million-song-dataset-mapping
Million Song Dataset to AcousticBrainz mapping. Jan 4, 2016. A well known dataset in MIR is the Million Song Dataset. It is useful to be able compare results between this dataset and AcousticBrainz, and so we provide a mapping of IDs between the two datasets. We currently have a mapping for about 250,000 MSD IDs, resulting in 370,000 matches (because a MSD ID may map to more than one MusicBrainz ID). See the README.md file in that directory for more information on how to run it.
Mining metadata from the web for AcousticBrainz (DLfM 2016)
http://labs.acousticbrainz.org/dlfm2016
Mining metadata from the web for AcousticBrainz (DLfM 2016). Aug 12, 2016. One of our research goals is mining music annotations and creation of annotated datasets. For the 3rd International Digital Libraries for Musicology workshop. We presented a new project which we are using to collect music metadata to improve the quality of data that we generate using AcousticBrainz. Read the paper here. MetaDB is our service for collecting metadata from different websites. We currently have scrapers for. Genre, su...
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Detailed Statistics - AcousticBrainz
http://acousticbrainz.org/statistics-graph
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Contribute - AcousticBrainz
http://acousticbrainz.org/contribute
In order to contribute acoustic data to AcousticBrainz, you will need to have a music collection that contains MusicBrainz IDs. This usually means that your collection will need to have been tagged with a MusicBrainz aware tagger like Picard. Or other MusicBrainz enabled taggers. If you have a collection of music files with MBIDs, please use one of the submission tools. Contributing Code / Documentation. The audio analysis engine that underpins AcousticBrainz. We have a list of ideas. If you find a bug i...
Recording "The Nutcracker: Act II (conclusion), no. 14. Pas de Deux: The Prince and the Sugar-Plum Fairy: Variation 2: Dance of the Sugar-Plum Fairy" by Royal Philharmonic Orchestra, Vladimir Ashkenazy - AcousticBrainz
http://acousticbrainz.org/0e1588e3-bbee-4946-90e1-3e27a6e9027b
Recording "The Nutcracker: Act II (conclusion), no. 14. Pas de Deux: The Prince and the Sugar-Plum Fairy: Variation 2: Dance of the Sugar-Plum Fairy" by Royal Philharmonic Orchestra, Vladimir Ashkenazy. The Nutcracker: Act II (conclusion), no. 14. Pas de Deux: The Prince and the Sugar-Plum Fairy: Variation 2: Dance of the Sugar-Plum Fairy. Royal Philharmonic Orchestra, Vladimir Ashkenazy. Tchaikovsky: The Nutcracker / Glazunov: The Seasons. Submission #1 out of 4. E minor (62.0%).
Recording "Messa da Requiem: 2. Dies irae: Lacrymosa dies illa" by Wiener Philharmoniker, Herbert von Karajan - AcousticBrainz
http://acousticbrainz.org/8c78b708-be52-4a65-bec2-134ba1f03ee7
Recording "Messa da Requiem: 2. Dies irae: Lacrymosa dies illa" by Wiener Philharmoniker, Herbert von Karajan. Messa da Requiem: 2. Dies irae: Lacrymosa dies illa. Wiener Philharmoniker, Herbert von Karajan. Submission #1 out of 6. A# minor (86.0%). Voice, timbre, gender, etc.
Recording "Bjango" by Lucky Monkeys - AcousticBrainz
https://beta.acousticbrainz.org/d18b40c3-e7ed-4168-8ea5-2ff93b8475d8
Recording "Bjango" by Lucky Monkeys. Submission #1 out of 1. A# minor (63.0%). Help us improve quality of the data! To submit feedback on high-level results. Voice, timbre, gender, etc.
Recording "Symphonies of the Planets 5" by NASA Voyager Recordings - AcousticBrainz
https://beta.acousticbrainz.org/e7e76a09-2a5d-44ab-aa31-f5e7e9eb4481
Recording "Symphonies of the Planets 5" by NASA Voyager Recordings. Symphonies of the Planets 5. Symphonies of the Planets 5. Submission #1 out of 5. A# minor (40.0%). Help us improve quality of the data! To submit feedback on high-level results. Voice, timbre, gender, etc.
Recording "Parsifal: I. Aufzug. "Weh! Weh! ... Wer ist der Frevler?" (Knappen, Ritter, Gurnemanz, Parsifal)" by Herbert von Karajan, Berliner Philharmoniker, Peter Hofmann, Kurt Moll, Claes-Håkan Ahnsjö, Kurt Rydl, Marjon Lambriks, Anne Gjevang, He
http://acousticbrainz.org/77da3935-cbee-431c-9e00-6f6fb6dfe210
Recording "Parsifal: I. Aufzug. "Weh! Wer ist der Frevler? 34; (Knappen, Ritter, Gurnemanz, Parsifal)" by Herbert von Karajan, Berliner Philharmoniker, Peter Hofmann, Kurt Moll, Claes-Håkan Ahnsjö, Kurt Rydl, Marjon Lambriks, Anne Gjevang, Heiner Hopfner, Georg Tichy. Parsifal: I. Aufzug. "Weh! Wer ist der Frevler? 34; (Knappen, Ritter, Gurnemanz, Parsifal). Submission #1 out of 2. D# major (39.0%). Voice, timbre, gender, etc.
Downloads - AcousticBrainz
http://acousticbrainz.org/download
We have two clients (graphical and command-line) available for people to use to submit audio features to the AcousticBrainz database. These clients calculate a JSON file containing data about the audio and upload it to AcousticBrainz. We do not upload your audio. All of these downloads are self-contained and include a static binary to perform the audio analysis. See our FAQ. For more information on why we use static binaries. If they are not tagged, we recommend Picard. For Windows (32 bit and 64 bit).
Recording "The Nutcracker: Act II (beginning), no. 12b. Divertissement: Coffee (Arabian dance)" by Royal Philharmonic Orchestra, Vladimir Ashkenazy - AcousticBrainz
http://acousticbrainz.org/ea7937b9-9e31-4395-afc5-87e65432cc2d
Recording "The Nutcracker: Act II (beginning), no. 12b. Divertissement: Coffee (Arabian dance)" by Royal Philharmonic Orchestra, Vladimir Ashkenazy. The Nutcracker: Act II (beginning), no. 12b. Divertissement: Coffee (Arabian dance). Royal Philharmonic Orchestra, Vladimir Ashkenazy. Tchaikovsky: The Nutcracker / Glazunov: The Seasons. Submission #1 out of 4. G minor (74.0%). Voice, timbre, gender, etc.
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AcousticBrainz labs shows some of the work we are doing. For some recent projects, see below. Aug 12, 2016. Mining metadata from the web for AcousticBrainz (DLfM 2016). Aug 8, 2016. Aug 8, 2016. Cross-collection evaluation for music classification tasks (ISMIR 2016). Jul 1, 2016. Million Song Dataset Echo Nest mapping archive. Jan 4, 2016. Million Song Dataset to AcousticBrainz mapping.
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