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Toward an Understanding of Lyrics-viewing Behavior
While Listening to Music on a Smartphone
National Institute of Advanced Industrial Science and Technology
(AIST)
Kosetsu Tsukuda, Masahiro Hamasaki, Masataka Goto
WHY do people view lyrics?
Reasons
Frequency of Reasons
Conduct an online survey involving 206 participants
Investigate how often users view lyrics for each reason
Behavior Details
Provide functions according to users’ reasons for viewing lyrics:
- For Understanding, displaying diverse interpretations of lyrics
- For Singing and Karaoke, automatically judging singing skill
- For Language, enabling users to see the meaning of a word
in lyrics just by tapping the word
Investigate users’ detailed behavior in terms of three aspects
(e.g., in terms of timing, for each reason, do users tend to decide
to view lyrics before playing a song or after playing a song?)
 Timing: for reasons with high frequency in the “After” group,
enable users to quickly execute the corresponding functions
 Percentage: for a user who stops viewing lyrics within a short
time, provide information related to the played song
because she is likely bored
HOW do people view lyrics?
Analyze 23 million lyrics request logs for a year
Lyrics Viewing Logs
 Collect logs from an iOS application of a
Japanese online music service
 Logs include the timestamp, user ID, and song ID
 The application gets a song’s lyrics
only when a user explicitly requests them
 The dataset (LyLog) consists of
611,895 users, 214,434 songs, and 23,034,417 logs
 For comparison, music listening dataset of Last.fm (Lastfm)
consisting of 660 users, 718,466 songs, and 2,932,430 logs
Song ID
Lyrics
Basic Statistics
Distribution of the number of logs per song
 There are 𝑦𝑦 songs that
have 𝑥𝑥 logs
 LyLog is more biased to
popular songs: top 6.64%
of the popular songs
dominates 80% of whole
logs (34.8% for Lastfm)
Distribution of logs over the hours of the day
 People tend to view more
lyrics after coming back
home at night and before
going to bed
 Because viewing lyrics
requires users to interact
with the app more actively
Repeat Consumption
 Some smartphone applications for online
music services (e.g., Spotify and Apple Music)
have provided a function that enables a user
to view song’s lyrics while listening to the song
 Such a function will become one of the main
means for viewing lyrics, given the current
situation where music streaming services on
smartphones have become a mainstream format
for listening to music
Angel Baby / Betty
World Is Like A
Dream To Me
If Only You Live
With Me Now
Come Back To
Piece Of My Place
Various lyrics-related studies in MIR community
 Enable users to search for songs by words in lyrics
 Estimate the topics of lyrics for exploring songs
 Estimate the lyrics intelligibility for language learning
More fundamental question remains unexplored
 Why and how do people view lyrics?
 Investigate the behavior of viewing lyrics
on a smartphone while listening to music
It has been reported that a user often listens to the same song
repeatedly over time; what about lyrics viewing behavior?
Fraction of repeat consumption for each user
Transition of temporal gap between consumptions
 An average of 37.8% of
user’s viewed lyrics have
already been viewed by
the user (60.4% for Lastfm)
 Still high compared to
other domains (e.g., 26%
for watching videos)
 When a user repeatedly views the lyrics of a song,
the gap grows over time as she gets bored with it
 For such a user, recommend novel lyrics related in terms
of the topic to expand her interest to other songs
Reason The user wants to:
Confirmation Confirm what the artist sings
Understanding More deeply understand the lyrics
Singing Sing to herself (not in public)
Structure
Figure out the structure of the lyrics,
such as verse and chorus
Karaoke Practice for singing in public, as in karaoke
Boredom Get rid of her boredom by viewing lyrics
Language Learn a language with the lyrics
Writing Study for writing lyrics
𝑡𝑡
Small temporal gap Large temporal gap

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Toward an Understanding of Lyrics-viewing Behavior While Listening to Music on a Smartphone (ISMIR 2021)

  • 1. Toward an Understanding of Lyrics-viewing Behavior While Listening to Music on a Smartphone National Institute of Advanced Industrial Science and Technology (AIST) Kosetsu Tsukuda, Masahiro Hamasaki, Masataka Goto WHY do people view lyrics? Reasons Frequency of Reasons Conduct an online survey involving 206 participants Investigate how often users view lyrics for each reason Behavior Details Provide functions according to users’ reasons for viewing lyrics: - For Understanding, displaying diverse interpretations of lyrics - For Singing and Karaoke, automatically judging singing skill - For Language, enabling users to see the meaning of a word in lyrics just by tapping the word Investigate users’ detailed behavior in terms of three aspects (e.g., in terms of timing, for each reason, do users tend to decide to view lyrics before playing a song or after playing a song?)  Timing: for reasons with high frequency in the “After” group, enable users to quickly execute the corresponding functions  Percentage: for a user who stops viewing lyrics within a short time, provide information related to the played song because she is likely bored HOW do people view lyrics? Analyze 23 million lyrics request logs for a year Lyrics Viewing Logs  Collect logs from an iOS application of a Japanese online music service  Logs include the timestamp, user ID, and song ID  The application gets a song’s lyrics only when a user explicitly requests them  The dataset (LyLog) consists of 611,895 users, 214,434 songs, and 23,034,417 logs  For comparison, music listening dataset of Last.fm (Lastfm) consisting of 660 users, 718,466 songs, and 2,932,430 logs Song ID Lyrics Basic Statistics Distribution of the number of logs per song  There are 𝑦𝑦 songs that have 𝑥𝑥 logs  LyLog is more biased to popular songs: top 6.64% of the popular songs dominates 80% of whole logs (34.8% for Lastfm) Distribution of logs over the hours of the day  People tend to view more lyrics after coming back home at night and before going to bed  Because viewing lyrics requires users to interact with the app more actively Repeat Consumption  Some smartphone applications for online music services (e.g., Spotify and Apple Music) have provided a function that enables a user to view song’s lyrics while listening to the song  Such a function will become one of the main means for viewing lyrics, given the current situation where music streaming services on smartphones have become a mainstream format for listening to music Angel Baby / Betty World Is Like A Dream To Me If Only You Live With Me Now Come Back To Piece Of My Place Various lyrics-related studies in MIR community  Enable users to search for songs by words in lyrics  Estimate the topics of lyrics for exploring songs  Estimate the lyrics intelligibility for language learning More fundamental question remains unexplored  Why and how do people view lyrics?  Investigate the behavior of viewing lyrics on a smartphone while listening to music It has been reported that a user often listens to the same song repeatedly over time; what about lyrics viewing behavior? Fraction of repeat consumption for each user Transition of temporal gap between consumptions  An average of 37.8% of user’s viewed lyrics have already been viewed by the user (60.4% for Lastfm)  Still high compared to other domains (e.g., 26% for watching videos)  When a user repeatedly views the lyrics of a song, the gap grows over time as she gets bored with it  For such a user, recommend novel lyrics related in terms of the topic to expand her interest to other songs Reason The user wants to: Confirmation Confirm what the artist sings Understanding More deeply understand the lyrics Singing Sing to herself (not in public) Structure Figure out the structure of the lyrics, such as verse and chorus Karaoke Practice for singing in public, as in karaoke Boredom Get rid of her boredom by viewing lyrics Language Learn a language with the lyrics Writing Study for writing lyrics 𝑡𝑡 Small temporal gap Large temporal gap