Kawaii Game Vocalics: A Preliminary Model
Katie Seaborn

Katja Rogers

seaborn.k.aa@m.titech.ac.jp
Tokyo Institute of Technology
Tokyo, Japan

University of Amsterdam
Amsterdam, The Netherlands
k.s.rogers@uva.nl

Somang Nam

Miu Kojima

Toronto Metropolitan University
Toronto, Canada
somang.nam@torontomu.ca

Tokyo Institute of Technology
Tokyo, Japankojima.m.ap@m.titech.ac.jp

ABSTRACT

1

Kawaii is the Japanese concept of cute++, a global export with local
characteristics. Recent work has explored kawaii as a feature ofuser experience (UX) with social robots, virtual characters, andvoice assistants, i.e., kawaii vocalics. Games have a long history ofincorporating characters that use voice as a means of expressing
kawaii. Nevertheless, no work to date has evaluated kawaii gamevoices or mapped out a model of kawaii game vocalics. In this work,
we explored whether and how a model of kawaii vocalics maps
onto game character voices. We conducted an online perceptions
study (N=157) using 18 voices from kawaii characters in Japanesegames. We replicated the results for computer voice and discovered
nuanced relationships between gender and age, especially youthfulness, agelessness, gender ambiguity, and gender neutrality. We
provide our initial model and advocate for future work on character
visuals and within play contexts.

Kawaii is the Japanese term for "cute," but it is also much more thanthat. Kawaii refers to impressions of cuteness, endearment, andeven pity. As a psychosocial factor of perception and experience,
kawaii has been linked to cognition, behaviour, and emotion [37]within and beyond its native Japan [9, 42]. As a global phenomenon,
kawaii has been adopted across a range of media around the world.
Within the games space, kawaii can be attributed to series such as
Pokémon, Animal Crossing, Kirby, and Super Mario Bros., as well asa wealth of other Japanese and Japanese-adjacent games [21, 48, 53].
Perhaps the most famous kawaii game characters include Pikachufrom Pokémon, the titular character of the Kirby series, and Toadfrom the Super Mario Bros. games. The appeal of these charactersis near-universal, speaking to the transnational and cross-culturalcharacteristics of kawaii.
Many kawaii game characters are judged based on their appearance and behaviour: the visuals. Yet, character voice may also
be a key feature of their kawaii appeal and lasting value. From
Pikachu’s eponymous "pika pika" to Toad’s vocal bursts, these vocalizations and speech patterns are instantly recognizable. Indeed,
recent work in human-computer interaction (HCI) has pointed tothe importance and dearth of work on kawaii sound [60], especiallyfor interactive characters like voice assistants [51]. Moreover, thegame context, with its complex audiovisual stimuli, may have special implications for kawaii vocalics, as there are many different
attributes to consider. Voice can be direct intelligible speech orunintelligible gibberish (e.g., Simlish), presented in tandem withcharacter animations. Characters can grunt or bark out lines (brief
exclamations) or let out non-linguistic vocal bursts. Non-voicing
sound techniques–type-writer or chalkboard sounds accompanying dialogue boxes1 –are also used. Voices and vocal expressions
can appear to originate from within the game world (i.e., a visible
character, often with speech animation), or present without a clear
source in the game world (e.g., in menu interfaces or for characters
not visible in the scene); while a matter of interpretation, this can beseen as a diegetic/non-diegetic distinction [8]. Further, perceptionof vocalics (kawaii or otherwise) could interplay with dynamic andstatic visual character attributes, speech content (if applicable), andother auditory elements in the game (e.g., music or ambient noises).
A model of kawaii game vocalics would offer a map of specific vocal
attributes distinct from, but related to, other aspects of the gamecharacter known (or theorized) to invoke perceptions of kawaii,

CCS CONCEPTS• Human-centered computing → Human computer interaction (HCI); • Applied computing → Computer games; Psychology; • Hardware → Sound-based input / output.

KEYWORDS
kawaii vocalics, kawaii, cuteness, vocalics, voice UX, game audio,
user experience
ACM Reference Format:
Katie Seaborn, Katja Rogers, Somang Nam, and Miu Kojima. 2023. Kawaii
Game Vocalics: A Preliminary Model. In Companion Proceedings of theAnnual Symposium on Computer-Human Interaction in Play (CHI PLAY
Companion ’23), October 10–13, 2023, Stratford, ON, Canada. ACM, New
York, NY, USA, 7 pages. https://doi.org/10.1145/3573382.3616099

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https://doi.org/10.1145/3573382.3616099

INTRODUCTION

1 E.g., https://www.youtube.com/watch?v=B3S9QCCMPRw

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Seaborn et al.

notably visual appearance and behaviour. This would increase ourunderstanding of the relationship between vocal attributes or acoustical features and other well-studied game character features, andcould be used by designers, researchers, critics, and even game fans
who may be experimenting with new voice-generating technologies in gaming spaces on YouTube and Twitch [23]. As yet, kawaii
game character voices are virtually unexplored.
In this preliminary work, we propose an initial model of kawaii
game vocalics: vocal features that lead to perceptions of kawaii inor through voices. Our goal was to motivate kawaii game vocalics
as a new area of study in game user research by way of an initialmodel and empirical evidence of kawaii perceptions of in-gamecharacter voices. To this end, we conducted an online perceptions
study using a range of stimuli sourced from popular kawaii gamecharacters in Japan. We asked two foundational research questions
to elucidate the presence and perception of kawaii game vocalics. First, we asked RQ1: Are the voices of game characters deemedkawaii (implicitly by way of their visual appearance) also perceived
as kawaii? Second, we asked RQ2: Do these perceptions depend on
the "girlish" qualities of the voices? This question was motivatedby two models of kawaii: the initial model of kawaii vocalics forcomputer voice [51], comprised of agedness (young), genderedness(girlish or ambiguous), language fluency, and anthropomorphism,
and the original two-layer model of kawaii [38], comprised of visual
cuteness and reactions to cuteness as a foundation alongside otherperceptual attributes of the kawaii source, such as friendliness,harmlessness, and prettiness. Our contributions are (i) empiricalevidence of kawaii voice perceptions in game characters based on
audio stimuli alone; (ii) confirmation of the initial model of kawaii
vocalics for game characters; and (iii) a data set of kawaii vocalics
ratings for game characters. This work sets the stage for a newresearch agenda within the broader area of game sound and contributes to the games research community’s understanding of a
popular mode of expression in people and characters that, being
associated with sexist and ageist attitudes [51, 54], is still policed,
discredited, and sidelined.

2 THEORETICAL BACKGROUND
2.1 A Psychosocial Model of Kawaii for Visuals
and Voice
Kawaii and cuteness as research phenomena have a relatively recent history with modern foundations2 . Perhaps the first instanceof "cute" being taken seriously as an object of study was by Lorenze
in the earlier part of the last century [22, 37]. Lorenze proposed thatperceptions of cuteness were linked to "baby schema" or Kindchenschema, referring to our innate reaction to the appearance of young
animals, humans and otherwise: the roundness of features, largeeyes, small mouths and noses, and so on. Nittono and colleagues[37–42] later developed a two-layer model of kawaii as (i) positive
emotions or affective responses that stem from (ii) features of thesocio-cultural environment. Kawaii illustrates how phenomena that
may originally relate to innate responses, i.e., Kindchenschema, areculturally influenced and socially mediated. The particular featuresof the Japanese sociocultural context, notably amae, or a desire for
2 A history of kawaii is out of scope for this paper; we refer the reader to Shiokawa[54] and Seaborn et al. [51], in ascending order of currency.

203

acceptance, and chizimi shikou, or a preference for small things,
highlight his interplay. Kawaii is now a decades-long cultural trend,
firmly established in Japan but also embraced around the world: across-cultural phenomenon.
The two-layer model of kawaii is made up of a stimulus, suchas a kawaii object, which has attributes deemed kawaii, such as
Kindchenschema, smiles, and colours, that are perceived in certain
ways, such as cute, pretty, and gentle, leading to cognitive appraisalsof the stimuli as kawaii. These appraisals are revealed throughemotional or affective responses, which can manifest subjectively(e.g., attitudes, thoughts), behaviourally, or physiologically. Thus
we can chart a kawaii response to a given stimuli. Nevertheless,kawaii has essentially been explored as a visual phenomenon [51],with only a few exceptions on nonverbal sounds and melodies[60], touch [43], behavioural conduct [24, 25], and voice [24, 51].
As Seaborn et al. [51] point out, this leaves open the question ofwhether and how other modalities, notably sound, fit into the twolayer model of kawaii. We attempt to explore this within the context
of games that feature kawaii voices.
The notion of kawaii has shifted over time, from its origins as pity
for the weak to a non-threatening and endearing quality of people,
non-human animals, and even objects [38]. This has implications
for games, as many characters–especially kawaii characters–are nothuman or even particularly humanlike, e.g., Pikachu, Kirby, Toad.
Nevertheless, voice is an anthropomorphic, or at least biomorphic,
feature not typically attributed to objects and generally associatedwith human-likeness [50]. Indeed, the initial model of kawaii vocalics provided evidence that human-likeness is key for kawaii
perceptions in voice assistants. As such, we would expect that thegame voices deemed most kawaii would also be the most humanlike
and least artificial or machinelike. We thus hypothesized:
H1. Perceptions of voice kawaiiness link to perceptions of low artificiality and high anthropomorphism.
Kawaii has also been conceptualized as a "girlish" phenomenonor feature of expression. This has led to its dismissal as a serious
topic by some [17, 38] and warnings of underlying sexism by others[51, 54]. At the same time, Nittono and colleagues have generally
approached kawaii in a gender-neutral way, as well as provided
some evidence of agelessness in the form of smiling elders deemedkawaii [40]. Seaborn et al. [51], focusing on voice phenomena, foundpreliminary evidence that gender ambiguity may be perceived as
most kawaii for certain individuals. However, given that the voices
deemed gender ambiguous were also deemed young, it is not clear
to what extent gender, age, or the combination of the two explain
perceptions of ambiguity. We attempt to further explore and distinguish the intersection of age and gender by including voices fromhuman and non-human game characters. We thus hypothesized:
H2. Perceptions of voice gender will link to kawaii by
way of femininity, i.e., gendered feminine.
H3. Perceptions of voice age will link to kawaii by
way of youthfulness, i.e., aged young.
H4. Perceptions of voice "girlishness" (feminine, young)will link to high kawaii ratings.

Kawaii Game Vocalics: A Preliminary Model

2.2

CHI PLAY Companion ’23, October 10–13, 2023, Stratford, ON, Canada

Theorizing Kawaii Game Vocalics within
Game Audio Studies

We approach kawaii game vocalics as a matter of perceiving auditory objects that are meaningful and may result in a variety ofperceptions, cognitions, behaviours, and other reactions [13]. Voicein games is multifarious and can be situated within a range of gameaudio taxonomies. A common distinction concerns audio diegesis[18, 20, 31, 56]. For example, a voice’s source of origin within thegame world (tied to a visible character vs. disembodied) can influence whether it is considered diegetic or non-diegetic. Liljedahl[20] distinguishes between speech and dialogue, sound effects, andmusic. Some vocal audio in games would fit into the speech and dialogue category, but others (e.g., non-linguistic vocal bursts) could
fit into the sound effects category, which, according to Friberg and
Gärdenfors, refers to character, avatar, ambient, and ornamental
sounds [10]. All can involve vocal elements (e.g., general background noise of a crowd speaking—termed walla if unintelligible).
In a master’s thesis, Holmes [16, p.30] categorized dialogue as main
dialogue, reaction & guidance lines (extending the former), ambient
dialogue (background dialogue), walla (unintelligible ambient dialogue), combat barks (orders, commands, reactions b/w combatants),
and emotes (“non-linguistic vocalisations such as screams, effort
grunts, or breathing”), although it is unclear how this categorization
was sourced or derived.
Much work has been done on voice interaction in audio research(e.g., in games [1], voice assistants [5, 57], and robots [27, 59]).
Still, more work is needed on design guidelines for voice interface
design [29]. Indeed, the vocal design of game characters and how
voice impacts impression formation is a significant research gap.
Voices have certain characteristics that can convey emotions [30,47], impact trust in the speaker [59], and influence perceptionsof the personality [4, 26]. This impression formation is driven bycharacteristics like frequency or pitch [26], harmonic-to-noise ratio[26], and speaking rate or intonation [4]. However, we know very
little about how this works for game characters, and how acousticalfeatures in the voices of game characters contribute to players’
impression of those characters.
Voice designers and voice actors in the games industry have a
lot of training and experience in how to elicit certain impressions
through vocalics. Indeed, such audio design and production roles
are of growing importance3 . For example, professional voice (andmotion capture) actors employ a full range of dramatic repertoire
for character motion and vocal characteristics, such as intensity
through physical exertion (e.g., by doing push-ups before or holding weights while recording4 ). But non-linguistic speech (gibberish
or vocal bursts) can also portray emotions (e.g., Bastion’s melodic
beeping in Overwatch [3]). Developing an empirical understanding of the vocal factors that can yield specific impressions could
help (voice) audio practitioners hone their craft more quickly andcontribute to basic knowledge.

3

METHODSWe carried out an online user perceptions study using the research
designs on visual [40] and voice-based [2] phenomena, aiming to

replicate the kawaii vocalics study by Seaborn et al. [51] with voicestimuli from game characters. Our protocol was registered before
data collection on May 11th , 2023 via OSF5 and approved by the
research ethics board at the first author’s institution.

3.1

Participants and Recruitment

Respondents (N=162) were recruited through Yahoo! Crowdsourcing Japan on June 12th , 2023. Five incomplete responses were removed. The final set of participants (N=157) included women (n=76,
one transgender), men (n=73), and none of another gender, whileeight preferred not to say. Most were aged 45-54 (n=49) or 3544 (n=42), with some older (55-64 n=29, 65-74 n=11, 75+ n=2) andyounger (18-34 n=16); eight preferred not to say. Most played games
every day (n=49, 31%), while others played games multiple times aweek (n=38, 24%), others never did (n=24, 15%), some played oncea week (n=14, 9%) or once a month (n=13, 8%), and others used toplay games but stopped (n=11, 7%), with eight preferring not to say.
Participants were paid at ∼1200 yen per hour, equating to ∼300 yen
for the study duration.

3.2

Procedure

Participants were given a link to a SurveyMonkey questionnaire
containing the consent form, stimuli and rating scales, and demographic questions. After consenting on the first page, they were
presented with the clips of game character voices, one voice perpage (cf. Section 3.3). They were asked to rate these stimuli basedon various vocal and social qualities related to kawaii (cf. Section
3.4). The stimuli were presented in a random order to avoid novelty
and order effects [49]. Demographics were collected on the final
page to avoid priming effects [15]. The study took ∼16 min.

3.3

Materials

We selected 18 voices using a three-step process. Initially, we attempted to identify game character voices deemed kawaii by experts
and novices on magazines, websites, and social media. However,many focused on the voice actors, who were known beyond games
and may have been judged based on their status as idols and celebrities in Japan. We also recognized that people may not associate
kawaii with voice, given the lack of work on non-visual kawaii sofar. We then instead identified game characters deemed kawaii ingeneral, using the same methods. Finally, we relied on our expertise
to manually add characters that were missed. All authors decided
on a final set of voice stimuli from all three steps that: (i) reflected
a range of ages, genders, and vocal types for verifying our hypotheses; (ii) were diverse in terms of game of origin, i.e., representing
a range of game types and particular game series or offerings; (iii)
were similar in terms of game origin, e.g., Toad and Toadette; and(iv) where we could isolate the voice against any background soundor music. The first author recorded 2- to 20-minute voice clips fromvideos containing the original voices. From these, a diverse sample
of vocal expressions were chosen and arranged into ∼8-second clips.
The final set is in Table 1.

3 https://blog.audiokinetic.com/en/a-speed-run-through-the-world-of-voice-design/
4 https://www.youtube.com/watch?v=8sZMSBtSFrg

5 https://osf.io/7tr6b204

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3.4

Seaborn et al.

4.2

Instruments and Measures

All instruments used a 5-point Likert scale unless noted. The item
order was randomized to curtail order effects [49]. All items weretranslated into Japanese by a native speaker, and then back-translated
into English and checked with an advanced speaker and native
speaker. The full questionnaire was pilot tested with six native
Japanese speakers.
3.4.1 Kawaii Perceptions. In the absence of a validated measure,
we used the one-item scale created by Seaborn et al. [51], which asks
for an agreement rating of kawaii-ness. Given that it is a one-item
scale, it was operationalized as a mean greater than 3.5 (skewed
towards agreement on kawaii-ness) and a median of 4 or above(nominal agreement). Marginal cases, where only one or the otherof these metrics were met, are noted.
3.4.2 Perceptions of Anthropomorphism, Artificiality, and Fluency.
We used the one-item humanlikeness scale from Baird et al. [2].
Following Seaborn et al. [51], we divided the item into two items
based on the poles (humanlike and artificial). We also added theitem on language fluency, key for the kawaii vocalics model [51].
3.4.3 Age Perceptions. Agedness was captured in a nominal scale:infant/baby (0-2 years), child (3-12 years), teenaged (13-19 years),
adult (20-39 years), middle-aged (40-64 years), older adult (65+years), and ageless.
3.4.4 Gender Perceptions. Genderedness was captured in a nominal scale: feminine, masculine, aspects of both (reported as ambiguous), and neither (reported as neutral). Participants could also enter
another option (free text).
3.4.5 Demographics. We collected gender, age, education, andgame use frequency.

3.5

Data Analysis

We used descriptive statistics to group voices by perceived age (baby,
child, teen, adult, ageless) and gender (masculine, feminine, genderambiguous, gender neutral). When Shapiro-Wilks tests showed
non-normal distributions, we used non-parametric statistics, e.g.,
Kendall’s tau correlations. We also used Bonferroni corrections.

4

RESULTS

Descriptive statistics are summarized in Table 1. We now report on
the hypotheses and full descriptive results.

4.1

H1. Perceptions of voice kawaiiness link toperceptions of low artificiality and highanthropomorphism.

A strong, negative correlation was found between Artificial and
Humanlike ratings (𝜏b = -.725, p < .05). A moderate positive correlation was found between Kawaii and Humanlike ratings (𝜏b =.356, p < .05). A moderate, positive correlation was found between
Humanlike and Fluent ratings (𝜏b = .571, p <.05), and a moderate,
negative correlation was found between Artificial and Fluent ratings (𝜏b = -.480, p < .05). No others were found. As before [51], we
can accept the hypothesis that the most kawaii voices werealso the most fluent, humanlike, and least artificial.

205

H2. Perceptions of voice gender will link tokawaii by way of femininity, i.e., genderedfeminine.

A Chi-Square test found a statistically significant association between Perceived Gender and Kawaii ratings across all voices, 𝜒 2 (16,2826) = 489.66, p < .05, 𝜙 = .208. Follow-up Chi-Square test of independence (Bonferroni corrected) showed relationships between
Perceived Gender and Kawaii ratings for all categories: Feminine(M=3.8, SD=.8, MD=4, IQR=1), Ambiguous (M=3.4, SD=1, MD=4,
IQR=1), Masculine (M=3.0, SD=.9, MD=3, IQR=2), Neutral (M=2.7,
SD=1.1, MD=3, IQR=2), p < .05. No voice was classified as ‘Other’across participants. A Kruskal-Wallis test indicated a significant
difference by gender category, 𝜒 2 (4) = 365.05, p < .05, with a Dunn’s
test (Bonferroni corrected) revealing significant differences acrossall gender categories. As with computer voices [51], we can accept
the hypothesis that voices deemed feminine were perceived
as the most kawaii.

4.3

H3. Perceptions of voice age will link tokawaii by way of youthfulness, i.e., aged
young.

A Chi-Square test found a significant relationship between Perceived Age and Kawaii ratings across all voices, 𝜒 2 (24, 2826) =404.52, p < .05, 𝜙 = .189. A Kruskal-Wallis test indicated a significant difference by age category, 𝜒 2 (5) = 226.91, p < .05, with aDunn’s test (Bonferroni corrected) revealing significant differences
across all age categories except for Baby-Child and Teen-Adult:
Teen (M=3.8, SD=.8, MD=4, IQR=1), Adult (M=3.7, SD=.9, MD=4,
IQR=1), Child (M=3.5, SD=1.0, MD=4, IQR=1), Baby (M=3.4, SD=1.0,
MD=4, IQR=1), and Ageless (M=2.7, SD=1.1, MD=3, IQR=2). As
before [51], we can accept the hypothesis that kawaii is anage-based phenomenon, linked to voice youthfulness.

4.4

H4. Perceptions of voice "girlishness"(feminine, young) will link to high kawaii
ratings.

Chi-Square tests found a significant relationship between Perceived
Age and Kawaii rating for feminine voices, 𝜒 2 (24, 1256) = 121.84,
p < .05, 𝜙 = .156, gender ambiguous voices, 𝜒 2 (24, 942) = 116.46,
p < .05, 𝜙 = .176, and gender neutral voices, 𝜒 2 (20, 314) = 37.99,
p < .05, 𝜙 = .174, but not masculine voices. A Kruskal-Wallis testfor voice and gender classifications revealed significant differencesin Kawaii ratings, 𝜒 2 (7) = 369.174, p < .05. A Dunn’s test (Bonferroni corrected) indicated this for all pairs except Feminine-Childand Feminine-Teen, Feminine-Child and Feminine-Adult, FeminineTeen and Feminine-Adult, Ambiguous-Baby and Ambiguous-Child:
Masculine-Child (M=3.0, SD=.9, MD=3, IQR=2), Feminine-Child(M=3.8, SD=.9, MD=4, IQR=1), Feminine-Teen (M=3.8, SD=.8, MD=4,
IQR=1), Feminine-Adult (M=3.7, SD=.9, MD=4, IQR=1), AmbiguousBaby (M=3.4, SD=1.0, MD=4, IQR=1), Ambiguous-Child (M=3.4,
SD=1.1, MD=4, IQR=1), Neither-Ageless (M=2.7, SD=1.1, MD=3,
IQR=2). We can accept the hypothesis of kawaii as girlish but
also gender ambiguous and gender neutral, confirming previous work [51] and demarcating gender neutrality.

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CHI PLAY Companion ’23, October 10–13, 2023, Stratford, ON, Canada

Table 1: Descriptive statistics for perceptions of kawaii, age, and gender in game character voice, in order of kawaii ratings
CharacterGame or Series

Kawaiiness

Age Group

Gender Group

BarbaraPikachu
Edea
Ayaka
QiQi
Peach
Kirby
AshleyZelda
Jigglypuff
Toadette
Yoshi
Young Link
Baby Bowser
Toad
Inkling GirlLuma
Shizue𝑎Genshin Impact [28]The Pokémon series, e.g., [12]Bravely Default [55]Genshin Impact [28]Genshin Impact [28]The Super Mario series, e.g., [36]The Kirby series, e.g., [14]The Wario series, e.g., [35]TLoZ series, e.g., [34]The Pokémon series, e.g., [11]The Super Mario series, e.g., [36]The Super Mario series, e.g., [36]TLoZ series, e.g., [32]The Super Mario series, e.g., [36]The Super Mario series, e.g., [36]Splatoon 3 [7]Super Mario Galaxy [6]Animal Crossing, e.g., [33]

Y: M=4.2, SD=.7, MD=4
Y: M=4.2, SD=.7, MD=4
Y: M=3.9, SD=.7, MD=4
Y: M=3.9, SD=.9, MD=4
Y: M=3.9, SD=.8, MD=4
Y: M=3.7, SD=.8, MD=4
Y: M=3.7, SD=.8, MD=4
Y: M=3.7, SD=.8, MD=4
Y: M=3.6, SD=.8, SD=4
M: M=3.4, SD=1, MD=4
M: M=3.4, SD=.9, MD=4
M: M=3.3, SD=1, MD=4
N: M=3.2, SD=.9, MD=3
N: M=2.9, SD=1, MD=3
N: M=2.9, SD=.9, MD=3
N: M=2.7, SD=1, MD=3
N: M=2.7, SD=1, MD=3
N: M=2.6, SD=1, MD=3

Child (MD=2, 60%)
Child (MD=2, 50%)
Teen (MD=3, 48%)
Adult (MD=4, 87%)
Child (MD=2, 58%)
Teen (MD=3, 43%)
Child (MD=3, 69%)
Teen (MD=3, 68%)
Adult (MD=4, 63%)Child (MD=2, 45%)
Child (MD=2, 59%)
Baby (MD=2, 57%)
Child (MD=2, 62%)Child (MD=2, 35%)
Child (MD=2, 55%)
Child (MD=2, 41%)
Ageless (MD=7, 76%)
Ageless (MD=7, 70%)

Fem. (MD=2, 97%)
Amb. (MD=2, 97%)
Fem. (MD=2, 87%)
Fem. (MD=2, 99%)
Fem. (MD=2, 94%)
Fem. (MD=2, 92%)
Amb. (MD=3, 51%)
Fem. (MD=2, 96%)Fem. (MD=2, 98%)
Amb. (MD=3, 43%)
Fem. (MD=2, 55%)
Amb. (MD=3, 53%)
Masc. (MD=1, 55%)
Amb. (MD=3, 45%)
Masc. (MD=1, 54%
Amb. (MD=3, 41%)
Neu. (MD=4, 69%)
Neu. (MD=4, 57%)

Y: Yes. M: Marginal. N: No. TLoZ: The Legend of Zelda. Fem.: Feminine. Masc.: Masculine. Amb.: Ambiguous. Neu.: Neutral. 𝑎 Isabella.

5 DISCUSSION
5.1 Kawaii Beyond Game Character VisualAppearance (RQ1)

Yoshi (Baby-Ambiguous) juxtapose the low kawaii Luma (AgelessNeutral) and Shizue (Ageless-Neutral). Toadette aside, all clips werevocal bursts or gibberish. Future work can explore biomorphism
and vocal types against these factors in kawaii voice phenomena.

The results indicate that game character voices, even in the absenceof other cues, especially visuals, can invoke a feeling of kawaii. In
short, people can "hear cute." This gives weight to the importance of
vocal design when creating game characters, especially if aiming fora kawaii impression. Yet, the level of kawaii varied across charactersand voices deemed kawaii in ways that relate to the factors in thegeneral and vocalics kawaii models, to which we now turn.

5.2

5.3

Limitations

We acknowledge several limitations. We conducted an online study
with a relatively small set of vocal stimuli. More stimuli from characters deemed kawaii or not need to be explored. Also, we did not
capture whether respondents knew the character belonging to thevoice. We thus cannot rule out the possibility that knowledge ofthe character and preexisting impressions of kawaii towards thatcharacter influenced results, which future work can tease out.

Is Kawaii "Girlish"? Confirming andAdvancing Models of Kawaii (RQ2)

We found the expected patterns based on the kawaii vocalics model[51] for this novel stimuli. We can confirm the extension to the twofactor model of kawaii for visual phenomena and social behaviour[38] by including the social identity [58] factors of gender and age,the computer agent factors of anthropomorphism and artificiality[2], and the voice UX factors of vocal expressivity and fluency [50].
We also confirm the results on age and gender ambiguity foundfor computer voice [51]. We also selected samples that allowed
us to explore gender neutrality. While not well distinguished [52],neutrality speaks to an absence of gender, while ambiguity speaks
to the potential of pluralistic gender/ing. These gender liminal perceptions may reflect generational shifts in attitudes towards thegenderedness of kawaii: less about "girl" and "boy" varieties [44] andmore about "individuality" [54]. The results for anthropomorphismin combination with the factors in Table 1 also hint at patterns ofliminiality for the non-human(oid) characters. The marginal casesof Jigglypuff (Child-Ambiguous), Toadette (Child-Feminine), and

206

5.4

Research Agenda

As with the source phenomenon, kawaii game vocalics likely haverepercussions for cognition, behaviour, and emotion that vary bygame character and context, as well as by individual player. Hereare some trajectories for future work:
5.4.1 Game Visuals: Of Character and Context. An ongoing issue
in research on game audio is that findings on audio perception captured outside of games do not necessarily translate within or acrossgames [46]. Research on computer agents has long indicated thatvoice and body can and often do intersect in ways that may be influenced by other features of the interactive context [50]. The visualappearance of the character, including animations and behaviours,
as well as the visual context, i.e., the visual game environment, willneed to be teased out in terms of whether and how perceptions ofkawaii in character vocalizations are influenced by relevant featuresof the game’s visual modalities.

CHI PLAY Companion ’23, October 10–13, 2023, Stratford, ON, Canada

Seaborn et al.

5.4.2 Towards a Taxonomy of Game Voice. Game voice–of characters and beyond–is complex and multifaceted. One of the challenges we encountered was finding a rigorously developed framework by which to select and categorize voice phenomena for data
analysis. This is a gap that needs addressing. The type of voice
phenomena–from vocal bursts to gibberish–and the presence orabsence of speech may affect kawaii perceptions. We relied on apreliminary taxonomy [16] and our general knowledge of how
voice phenomena is operationalized. The next step is to develop
a game context-oriented taxonomy using rigorous methods liketype-building analysis [19].
5.4.3 The Kawaii Vocalics Data Set: An Open Science Endeavour.
As a "first" next step, we have started and offer an open data set.
Like the ABOT (Anthropomorphic Robot Database) project [45],we aim to provide a database of psychosocial factors attributed to
specific voices. We provide our initial data set here: https://bit.ly/
kawaiigamevocalics

6

CONCLUSION

Kawaii game vocalics brings a fresh perspective to the fields ofgame audio research and voice interaction. Moreover, existing models of kawaii premised on visuals need to be expanded to include
voice UX factors. Experimental work on a variety of non/humanoid
characters and contexts will be needed–and there is a wealth ofgame material to draw on.

ACKNOWLEDGMENTS
This work was supported by department funds at Tokyo Instituteof Technology.

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