1,721,057 research outputs found
Fine-grained Vocal Imitation Set
No full textThis dataset includes 763 vocal imitations of 108 sound events. The sound event recordings were taken from a subset of Vocal Imitation Set (zenodo.org/record/1340763). While the original VocalImitationSet only contains vocal imitations of a single reference recording per class, this new dataset contains vocal imitations of multiple reference recordings per class. Class names and filenames in this dataset are matched with the VocalImitationSet. Read the following paper to get more detailed information about VocalImitationSet.
[pdf] Bongjun Kim, Madhav Ghei, Bryan Pardo, and Zhiyao Duan, "Vocal Imitation Set: a dataset of vocally imitated sound events using the AudioSet ontology," *Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018)*, Nov. 2018.
Contact Info:
- Interactive Audio Lab: http://music.eecs.northwestern.edu
- Bongjun Kim [email protected] | http://www.bongjunkim.com
- Bryan Pardo [email protected] | http://www.bryanpardo.com</p
Vocal Imitation Set v1.1.3 : Thousands of vocal imitations of hundreds of sounds from the AudioSet ontology
No full text<p>The VocalImitationSet is a collection of crowd-sourced vocal imitations of a large set of diverse sounds collected from Freesound (<a href="https://freesound.org/">https://freesound.org/</a>), which were curated based on Google's AudioSet ontology (<a href="https://research.google.com/audioset/">https://research.google.com/audioset/</a>). We expect that this dataset will help research communities obtain a better understanding of human's vocal imitation and build a machine understand the imitations as humans do.</p>
<p>See <a href="https://github.com/interactiveaudiolab/VocalImitationSet">https://github.com/interactiveaudiolab/VocalImitationSet</a> for more information about this dataset and its latest updates.</p>
<p>For citations, please use this reference:</p>
<p>Bongjun Kim, Madhav Ghei, Bryan Pardo, and Zhiyao Duan, "Vocal Imitation Set: a dataset of vocally imitated sound events using the AudioSet ontology," <em>Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018)</em>, Nov. 2018.</p>
<p>Contact Info:</p>
<p>- Interactive Audio Lab: <a href="http://music.eecs.northwestern.edu/">http://music.eecs.northwestern.edu</a></p>
<p>- Bongjun Kim <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bongjunkim.com/">http://www.bongjunkim.com</a></p>
<p>- Bryan Pardo <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bryanpardo.com/">http://www.bryanpardo.com</a></p>
Vocal Imitation Set v1.0 : Thousands of vocal imitations of hundreds of sounds from the AudioSet ontology
No full text<p>The VocalImitationSet is a collection of crowd-sourced vocal imitations of a large set of diverse sounds collected from Freesound (<a href="https://freesound.org/">https://freesound.org/</a>), which were curated based on Google's AudioSet ontology (<a href="https://research.google.com/audioset/">https://research.google.com/audioset/</a>). We expect that this dataset will help research communities obtain a better understanding of human's vocal imitation and build a machine understand the imitations as humans do.</p>
<p>See <a href="https://github.com/interactiveaudiolab/VocalImitationSet">https://github.com/interactiveaudiolab/VocalImitationSet</a> for the latest updates to this dataset.</p>
<p>Contact Info:</p>
<p>- Interactive Audio Lab: <a href="http://music.eecs.northwestern.edu/">http://music.eecs.northwestern.edu</a></p>
<p>- Bongjun Kim <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bongjunkim.com/">http://www.bongjunkim.com</a></p>
<p>- Bryan Pardo <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bryanpardo.com/">http://www.bryanpardo.com</a></p>
VimSketch Dataset
No full text<p>VimSketch Dataset combines two publicly available datasets, created by the <a href="http://music.eecs.northwestern.edu">Interactive Audio Lab</a>:</p>
<ol>
<li><a href="https://zenodo.org/record/1340763#.XI8fV9F7mCR">Vocal Imitation Set</a>: a collection of crowd-sourced vocal imitations of a large set of diverse sounds collected from Freesound (<a href="https://freesound.org/">https://freesound.org/</a>), which were curated based on Google's AudioSet ontology (<a href="https://research.google.com/audioset/">https://research.google.com/audioset/</a>).</li>
<li><a href="https://zenodo.org/record/1251982#.XI_YdtF7mCQ">VocalSketch Dataset</a>: a dataset containing thousands of vocal imitations of a large set of diverse sounds.</li>
</ol>
<p> </p>
<p>Publications by the Interactive Audio Lab using VimSketch:</p>
<p><a href="https://archivefda.dlib.nyu.edu/bitstream/2451/60758/1/DCASE2019Workshop_Pishdadian_51.pdf">[pdf]</a> Fatemeh Pishdadian, Bongjun Kim, Prem Seetharaman, Bryan Pardo. "Classifying Non-speech Vocals: Deep vs Signal Processing Representations," Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), 2019</p>
<p> </p>
<p>Contact information:</p>
<p>- Interactive Audio Lab: <a href="http://music.eecs.northwestern.edu/">http://music.eecs.northwestern.edu</a></p>
<p>- Bryan Pardo <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bryanpardo.com/">http://www.bryanpardo.com</a></p>
<p>- Bongjun Kim <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bongjunkim.com/">http://www.bongjunkim.com</a></p>
<p>- Fatemeh Pishdadian <a href="mailto:[email protected]">[email protected]</a> | <a href="http://www.bongjunkim.com/">http://www.fatemehpishdadian.com</a></p>
<p> </p>
<p> </p>
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
