Songrium: A Music Browsing Assistance Service with
Interactive Visualization and Exploration of
a Web of Music
Masahiro Hamasaki

Masataka Goto

Tomoyasu Nakano

National Institute of Advanced Industrial Science and Technology (AIST)
1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan

songrium-ml [at] aist.go.jp
ABSTRACT

and as such, various types of relations between musical entities can be found. Similarity relations, for example, include
those based on lyrics, melody line, chord progression, genre,
mood, musical instrument, etc. Derivative relations, suchas new arrangements, remixes, and covers, are also popular. These relations among songs form a large and complex
network which, in contrast to a web of documents, is not immediately accessible. For example, in the web of documents[6], hyperlinks allow people to quickly and automatically see
which documents are related to which. In a web of musicalworks, on the other hand, the lack of a tool for viewing relations among songs or music video clips precludes users from
exploring this rich and complex space.
In this paper we propose that with recent advances in
web-crawling, metadata analysis, music signal processing,machine learning, and data visualization techniques, we areclose to realizing a “Web of Music”. We demonstrate thisby describing a music browsing assistance service, Songrium(http://songrium.jp), which we have developed in order toallow users to explore music while seeing and utilizing various relations among music video clips on video sharing websites.
Although YouTube1 is the most popular video sharing service in terms of views and uploads of music video clips, there
are too many missing nodes and links to realize a web of musical works. The majority of the popular music content on
YouTube is commercial music, and most commercial music
video clips are uploaded for promotional purposes. Thesesongs/videos are usually created independently of the web
and subsequently uploaded as ﬁnished works. It is therefore
common, for example, for some works (nodes) and relations(links between works) by an artist to be missing.
In contrast, music content related to the singing synthesis
technology VOCALOID [14] on the most popular Japanese
video sharing service, Niconico2 , largely features content native to the web. The music and derivative content contained
within were born, listened to, and distributed on the web.
For this reason, we describe this type of music as web-native
music, which we believe to be the key factor in the formation of the Web of Music. The current main target ofSongrium is therefore original songs using VOCALOID andtheir derivative works on Niconico.

This paper describes a music browsing assistance service,
Songrium (http://songrium.jp), which increases user enjoyment when listening to songs and allows visualization andexploration of a “Web of Music”. We deﬁne a Web of Musicin this paper to be a network of “web-native music”, which
we deﬁne in turn to be music that is published, shared, andremixed (has derivative works created) entirely on the web.
Songrium was developed as an attempt to realize a Webof Music, by showing relations between both original songs
and derivative works and oﬀering an enriched listening experience. Songrium has analyzed over 600,000 music video
clips on the most popular Japanese video-sharing service,
Niconico, which contains original songs of web-native music
and their derivative works such as covers and dance arrangements. Analysis of over 100,000 original songs reveals thatover 500,000 derivative works were generated and have contributed to enrich the Web of Music.

Categories and Subject Descriptors
H.3.5 [Online Information Services]: Web-based services; H.5.5 [Sound and Music Computing]: Signal analysis, synthesis, and processing

General Terms
Design, Human Factors

Keywords
Web of Music, Web-native music, Music interface, Visualization, Web service, User-generated content

1.

INTRODUCTION

Despite being a creative process, composing a musicalpiece or music video clip is often inspired by existing work,

Copyright is held by the International World Wide Web Conference Committee (IW3C2). IW3C2 reserves the right to provide a hyperlink to theauthor’s site if the Material is used in electronic media.
WWW’14 Companion, April 7–11, 2014, Seoul, Korea.
ACM 978-1-4503-2745-9/14/04.
http://dx.doi.org/10.1145/2567948.2576944.

1
2

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http://www.youtube.com
http://nicovideo.jp

In the present paper, we describe the Web of Music as
seen through the lens of Songrium. After gathering andanalyzing over 600,000 video clips of web-native music from
Niconico, we found that web-native music has a strong powerof generating derivative works, which are ﬁve times morecommon than original songs. Interestingly, we found thatsome derivative works received more views than their original songs.

2.

WEB-NATIVE MUSIC ON NICONICO

We deﬁne music satisfying all the following three conditions to be web-native music:(1) It is generally assumed that new original songs are ﬁrst
released on the web (without CD release or radio play,for example), with a unique URL identifying the source
and release date.

Figure 1: The monthly number of published original songs and their derivative works in the period
September 2007 – August 2012.

(2) Creators do not hesitate to create and release derivative works of original songs on the web.

Table 1: Classification results of 517,024 derivative
works. Since some derivative works have multiple categories, the total number of classifications isgreater than the number of derivative works.
category# of works(a) Singing
346,192(b) Dancing
22,808(c) Arranging and Performing
30,76628,311(d) Featuring 3D characters(e) Creating Music video
8,174(f) Others
80,880(3) After releasing original or derivative works, their creators can publicly receive feedback on the web and be
encouraged to create more content.
The consequence of condition (1) is that everybody can instantly listen to new content and be assured of its source.
The lack of barriers to viewing content is clearly attractive
to people. Moreover, the identifying URL means that the
popularity and other statistics of web-native music can be
automatically tracked by systems such as Songrium. Condition (2) means that there is a huge potential to generatederivative works from original content, which is crucial to
the formation of a mature Web of Music. Marshall et al.
[16] reported that remixing and republishing can pose issues
in some web music, highlighting the need for web-native music to have well-deﬁned and accepted rules for the creation ofderivative works. The ﬁnal condition in our deﬁnition motivates creators to continue making new content and derivative works, forming a positive feedback loop for both creatorsand listeners. Satisfying all three conditions, VOCALOID
songs on Niconico are an ideal example of web-native music,
as outlined below.
VOCALOID is a singing synthesis technology [14] whichforms a subset of the music content creation community on
Niconico. This technology has begun to be used to synthesize the main vocal melody of songs, and many examples have been published as original works on the website.
Despite the impressive technology, the vocals produced by
VOCALOID are easily identiﬁable as not of human origin,meaning that both creators and listeners naturally accept
that these songs are ﬁrst published on the web. Niconico
therefore serves as a forum for VOCALOID creators andlisteners to coalesce. Furthermore, because page views andpublishing date are managed by the website, metadata caneasily be used to analyze the music content and provide
ranking of video clips based on page views, etc.
There are many diﬀerent products based on VOCALOID
and each product has a diﬀerent vocal timbre. Most products have an associated character image, with Hatsune Miku
3
being the most well-known. Right after releasing Hatsune Miku, Crypton Future Media (developer of Hatsune

Miku) oﬃcially started allowing users to reuse its character for derivative works with their original license: Piapro
Character License 4 . Following this, users started to create
music videos, such as promotion videos for musicians, withsuch original songs and drawings. Some users even went
as far as to create 3D models of Hatsune Miku and create
3D animation videos [9, 8]. Subsequently, many songwriters publish karaoke (full song without vocals) version of theirown original songs, prompting some users to sing these songs
and also publish derivative works recorded in video clips.
Niconico is one of the most popular video communication
services in Japan today. As with similar services (YouTube,etc.), users are able to upload and view videos, but Niconico has additional feature of a text communication which
overlays recent comments by anonymous users on the video,
synchronized to the video playback. These overlaid comments create a sense of a shared watching/listening experience, labelled by Satoshi Hamano as Pseudo SynchronizedCommunication. Essentially, users feel part of a community by viewing the impressions, interpretations and feelings
expressed in the comments. These time-synchronized comments also give feedback to creators from listeners and often
motivative the creation of new content.
Figure 1 shows the number of monthly published original songs and their derivative works from September 2007
to August 2012. In this paper, we deﬁne the term ‘derivative work’ to be a video clip reusing a part of or whole of3
http://www.crypton.co.jp/mp/pages/prod/vocaloid/
cv01_us.jsp

4
From December 2012, they use Creative Commons license
for foreign users.

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video clips, and music video clips with 3D animations. By
providing people with easy, intuitive access to those derivative works, Songrium allows them to not only ﬁnd interestingmusic video clips but also understand and respect creatorsof music and video clips.
Songrium uses web mining and music understanding technologies together with advanced data visualization techniques to achieve unique functions, such as Music Star Map,
Planet View, Bubble Player, and Singing Voice Analysis.

3.1 Music Star Map and Planet View
Music Star Map is a function that visualizes original songs.
Original songs are embedded in a two-dimensional space,mapped automatically based on audio feature similarity.
The position of a song on the map is such that songs inclose proximity have similar moods (estimated by audio feature analysis, see 4.2). Figure 3-(A) portrays a screenshotof this function. Furthermore, when a user clicks an original song on Music Star Map, its derivative works appear ascolorful icons and orbit the selected song. We call this view
“Planet View”. Figure 3-(B) shows a screenshot of Planet
View.
In Figure 3-(B), each circle icon denotes a derivative workwith attributes represented by the icon orbit, size, color,and velocity. The distance from the center is indicative of
the publishing date, with the most recent work in the outermost orbit. The size of each icon reﬂects the number ofpage views; the color indicates one of the following derivative categories: Blue (Singing), Red (Dancing), Green (Arranging and Performing), Purple (3D characters in music
video), Yellow (Creating music video), and White (Others).
Finally, the velocity (orbit speed) of an icon represents how
many times the content has been favourited by users of thesystem.
The oﬃcial embedded video player of the Niconico service is shown at the upper-right corner to play back a video
clip of the selected original song (Figure 3-(C)). Our musiclistening interface has a chorus-search function for trial listening, SmartMusicKIOSK [4], which is shown below theembedded player (Figure 3-(D)). Songrium has an original
social tagging framework called ‘Arrow Tag’ that allows toannotate a relation between music content [7]. Figure 3-(E)shows a list of Arrow Tags.

Figure 2: Re-using network of original songs andtheir derivative works in VOCALOID community
on Niconico.

video clip of VOCALOID original song. According to thisﬁgure, the number of uploaded original songs and derivative
works has been increasing rapidly. 14% of original songs
have a derivative work whose page view is higher than original work, indicating that derivative works are also attractive
content.
80% of derivative works are published after one monthof the original publication date, while 40% are publishedafter one year, showing that derivative works extend thelongevity of original works. Table 1 shows classiﬁcation
results of 517,024 derivative works of 108,215 VOCALOID
original songs that we gathered from Niconico. We deﬁned
six categories of derivative works: (a) Singing a song, (b)Dancing to a song, (c) Performing a song on musical instruments, (d) Featuring 3D characters in music video, (e)Creating a music video for a song, and (f) Others. The ﬁrst
three categories derived from oﬃcial categories from Niconico; the other two categories are derived from our previous
work [9, 8]. “Others” includes, for example, videos which
review or rank existing videos, or use VOCALOID songs as
the background music to other video content.
A reuse network of this large number of derivative works
in the VOCALOID community on Niconico forms a huge
directed graph where each node denotes a diﬀerent video
clip and each edge has a direction from derivative work to
an original work. Figure 2 shows a small excerpt of the hugereuse network in the VOCALOID community. This network
forms part of a Web of Music, but is not in plain sight forusers.

3.

3.2 Bubble Player
Bubble Player visualizes the history of VOCALOID songs.
It plays groups of associated songs published within a userspeciﬁed time frame on continuous playback. The interface
shows the growth in popularity of songs, arranged by published date, in an animated display and only plays songs thatsatisfy certain user-speciﬁed conditions (play count, etc.).
Thus, this feature allows users to experience a group of songs
in one continuous movie, giving a clear, intuitive picture of
how trends on video-sharing services behave.
Figure 4 shows a screen shot of Bubble Player and examples of animation. When a user speciﬁes a period, Songrium
displays groups of songs published during the speciﬁed period in chronological order, giving the user a full perspectiveon the trends and transitions in published song groups overtime. Each song is represented by a “bubble” (a colored
circle). New song bubbles appear in accordance with theirrespective published dates and congregate in an animation.
The colors of the bubbles correspond to the voice synthesis

SONGRIUM FOR VISUALIZATION OFWEB OF MUSIC

By visualizing the Web of Music, Songrium enables people to have a better understanding of various relations in
the web-native music and an enriched interactive experience
with the Web of Music. It was diﬃcult for people listening
to original songs to notice that there exist various derivative
works of them, such as cover versions, singing or dancing

525

Figure 3: Screenshot of the (A) “Music Star Map” and (B) “Planet View” interface in Songrium. The former
visualizes original songs; the latter their derivative works. Both are connected seamlessly. (A) All original
songs are arranged in a two-dimensional space with similar songs positioned in close proximity. Any particulararea can be expanded for viewing by double clicking, and then scrolled to by dragging. (B) After selecting an
original song on Music Star Map, users can view its derivative works rotating around the selected song in thecenter. (C) Embedded video player of Niconico for video playback. (D) Playback interface for trial listening(SmartMusicKIOSK). (E) Social annotated relations called Arrow tags [7] to and from this song instance.

library used in the VOCALOID software, while the sizes ofthe bubbles indicate play counts. Songrium also plays truncated chorus sections of certain songs that satisfy conditions
speciﬁed by the user, making it easy to see what kinds ofsongs were being published as more and more bubbles appear. In the background, the display shows pieces of text
describing related events.

VOCALOID on Niconico on a daily basis. These are thenclassiﬁed using the technique described in Section 4.1, andanalyzed in the audio domain in order to understand themusical content using the method described in Section 4.2.
The user interface is implemented using HTML5, SVG,JavaScript, the JavaScript library D3.js, and the embedded
video player of the Niconico service.
Songrium service was released to the public at http://songrium.jp on August 7, 2012. As of December 2013,108,215 original songs and 517,024 derivative works havebeen registered in Songrium.

3.3 Singing Voice Analysis“Singing a VOCALOID song” (in which a human singer
covers a VOCALOID song) is currently the most popular
category of derivative work. These derivative singing videos
represent one of the most-watched and most popular sets ofcontent on video-sharing services, with some original songs
having hundreds or even thousands of derivative singing
videos. The derivative singing videos for a given song are
all based on the same melody and song structure, meaning
their deﬁning characteristics lie solely in the properties ofvoice and vocal interpretations of the singers. Singing Voice
Analysis visualizes these derivative works based on measurements of male and female singing voice characteristics.
Figure 5 shows a screenshot of the Singing Voice Analysis. Red and blue circles in the middle of the screen
represent singing videos. The higher the circle (larger ycoordinate), the more feminine the singer’s voice; the lower
the circle (smaller y-coordinate), the more masculine thevoice. Through this visualization of voice properties, users
can browse a wide array of singing videos through the lensof vocal attributes.

4.

4.1 Classification of Video Clips
Every music video clip on Songrium is classiﬁed automatically as an original song or a derivative work. Because
Niconico supports social tags for each clip and tags of somekinds such as “Original Song” and “be enshrined in the Hallof Fame song” are usually put on original songs on Niconico,
we can rely on these tags. However, even if some original
songs have no such tag, Songrium automatically classiﬁesthem correctly by crawling a set of related web sites to generate the “white list” of VOCALOID original songs. In thecase of derivative works, these can be readily identiﬁed when
the description text of the video clip includes a hyperlink to
the original video clip from which it was derived. These hyperlinks almost always exist on Niconico because users liketo acknowledge the original video clip.
When a derivative work is incorporated, its relation tothe original song is estimated automatically. The derivative
works are classiﬁed into one of the six predeﬁned categories
described in Section 3.1. With the exception of category
Others all the remaining categories are extremely popularand have their own unique social tags on Niconico. Using

IMPLEMENTATIONSongrium consists of three components: a web crawler,
a web server, and a user interface. The web crawler automatically checks updated music video clips related to526

Figure 4: Screenshot of the “Bubble Player” ofSongrium showing various types of information. (F)Bubble animation intuitively shows how many songs
were published during a user-specified period. (G)Chorus playback and metadata of songs that satisfy
user-specified conditions. (H) User input form forplayback conditions. (I) Related events are shownin the background (sourced from open calendar dataon the web).

Figure 5: Screenshot of the “Singing Voice Analysis” of Songrium, showing visualization of the proportions of male-type and female-type vocals of asong’s derivative works. (J) Circles indicate derivative work. y−axis shows the vocal type; x-axis can bechanged from the left panel. (K) Users can choose
the order of the circle in the x-axis, e.g., numberof page views, publishing date, and so on. (L) Embedded video player of Niconico for derivative work
playback, featuring SmartMusicKIOSK.

these tags, Songrium can produce a reliable classiﬁcation ofderivative works.
Moreover, Songrium enables users to easily report an error
in any of the above classiﬁcation of video clips, extraction oflinks, or estimation of relations to further improve the user
experience.

audio-based F0 estimation method PreFEst [3]. Following
this, LPMCC (mel-cepstral coeﬃcients of LPC spectrum)of vocal and ΔF0 are estimated and then combined into asingle feature vector at each frame. Then, reliable frames
are classiﬁed as vocal by using a vocal/non-vocal GMM [2].
Finally, the male/female probabilities of each reliable
frame are estimated using a probabilistic Support Vector
Machine (SVM) [1], which are reduced to a single value by
taking the median across the SVM output.

4.2 Understanding Music in Video Clips
User interfaces of Songrium utilize not only web-mined
text metadata but also results of understanding audio signal on music content. This combination expands variety ofmusic browsing assistance.
Chorus sections and repeated sections are estimated byusing the audio-based chorus-section detection method RefraiD [4], which was also used as the back-end for the original SmartMusicKIOSK interface. By analyzing relations
between various repeated sections, the RefraiD method can
detect all the chorus sections in a song and estimate boththe start and end points of each section. It can also detect modulated (transposed) chorus sections, which are especially common in pop music.
The position of each original song is mapped to a twodimensional space of the Music Star Map based on analysis
of audio features. Although any feature vector designed forcomputing music similarity could be used, in our current implementation, we use a 200-dimensional audio feature vector
obtained using learned latent representations [10]. To determine the (x-y) position of a song on the Music Star Map,
its 200-dimensional feature vector is projected onto two dimensions using principal component analysis (PCA), where
only the ﬁrst two components are retained.
To estimate male and female singing voice characteristics
from singing video clips, we use a probability estimation
model with extracted reliable frames [2] including the vocal
part. In order to extract such frames from video clips with
polyphonic music, we ﬁrst estimate the melody using the

5. RELATED WORK
Songrium, at its core, is a music browsing assistance service. Most previous research into interactive music browsing focused on visualizations to explore musical collections[17, 18, 5, 21, 12]. Given the multiple dimensions associated with music data, one particular visualization techniqueoften attempted is visualization of a music collection in a
two-dimensional plane [17, 21, 12]. Our Music Star Map(see Section 3.1) is one particular example of this. Interactive interfaces are also important for user experiences; [5]assists a user in discovering songs and [18] assists a user inﬁnding artists. In contrast to the advances in interactive music browsing mentioned above, Songrium visualizes not only
original songs, but also their derivate works and respective
histories, facilitating the eﬀortless browsing of web-native
musical content.
Music recommendation [22][20] is an automated method
to give users the opportunity to encounter unfamiliar but potentially interesting songs. Songrium also assists such user
activities by visualizing the Web of Music. Kamalzadeh reports 50% of active listeners would like to choose songs one
after another [13]. Furthermore, just 9% use online recommendation and 10% use shuﬄe when listening to a collection.
This result indicates that active listeners enjoy not only listening songs but also choosing songs. On this point, visualiz-527

[7] M. Hamasaki and M. Goto. Songrium: A musicbrowsing assistance service based on visualization ofmassive open collaboration within music content
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2013, pages 4:1–4:10, 2013.
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ing the Web of Music can provide an excellent experience foractive listeners, having a complementary relationship withmusic recommendation.
Some researchers have also attempted to investigate linked
music data. Jacobson proposed music similarity ontology[11], while Raimond [19] and Kolozali [15] proposed an ontolgy to describe a process of creating music. The purposeof these studies was to construct a Web of Data for music.
On the other hand, our present research aims to investigate
and assist the existing Web of Music.

6.

CONCLUSIONSIn this paper, we proposed a new music browsing assistance service called Songrium that visualizes VOCALOID
music including original songs and their derivative works on
the video sharing site Niconico. Our target music content
was web-native music: music content that was born, listened
to, and distributed on the web. Songrium provides various
visualization tools to assist users in grasping the relations
among web-native music and also helps them discover newcontent. Speciﬁcally, Music Star Map shows audio similarity
relations and Planet View shows derivative relations. Bubble Player shows a history of web-native music content andSinging Voice Analysis helps users to ﬁnd derivative works
based on the characteristics of the sung voice.
For future work, we will continue to run the Songrium
service and improve it based on user feedback. In this paper, we mentioned only VOCALOID music, but web-native
music is available from many other sources, which we hope
to exploit in the near future.

7.

ACKNOWLEDGMENTS

We thank Keisuke Ishida for the web service implementation of Songrium and Matt McVicar for his helpful comments on earlier drafts of this paper. We also thank anonymous users of Songrium for editing social annotations. This
work was supported in part by CREST, JST.

8.

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