Emotion Without Words: A Comparison Study of Music and
Speech Prosody
L'émotion sans mots :Une étude comparative de la
prosodie musicale et de prosodie de la parole
Sarah Faber, BMT(Hons), MA, MTA
Research Assistant, Anglia Ruskin University, United Kingdom
Anna Fiveash, BPsy (Hons), MA
Doctoral Student, Macquarie University, Australia
Abstract
Music and language are two human behaviours that are linked through their
innateness, universality, and complexity. Recent research has investigated
the communicative similarities between music and language and has
found syntactic, semantic, and emotional dimensions in both. Emotional
communication is thought to be related to the prosody of language and the
dynamics of music. The purpose of this study was to investigate whether
language's prosody can successfully communicate a phrase's emotional
intent with the lexical elements of speech removed, and whether the results
are comparable with a musical phrase of the same perceived emotion.
Eighty-five participants ranked a selection of emotional music and prosodic
vocalizations on scales of happy and sad. Results showed consistency and
correctness in the emotional rankings; however, there was higher variance
and lower intensity in the speech examples across all participants and
more consistency in music examples among musicians compared to nonmusicians.
This study suggests that speech prosody can communicate a
phrase’s emotional content without lexical elements and that the results are
comparable, though less intense, than the same emotion conveyed by music.
This study has implications for the field ofmusic therapy through support for
the accurate identification of emotional information in non-verbal stimuli.
Keywords: music therapy, prosody, emotion, language, music,
semantics, dynamics
CanadianJournal ofMusic Therapy ooRevue canadienne de musicothérapie, 20(2), 86
Résumé
La musique et le langage sont deux comportements humains liés par leur
complexité et leur universalité innée. La recherche récente a examiné les
similarités se rapportant à la communication entre la musique et le langage et
des dimensions syntaxiques, sémantiques et affectives ont été décelées dans
les deux cas. Il est usuel de penser que la communication affective est reliée
à la prosodie de la parole ainsi qu’aux dynamiques musicales. Le but de cette
étude est d’examiner si la prosodie de la parole peut réussir à communiquer
une phrase contenant une intention affective sans les éléments lexicaux de la
parole et si les résultats sont comparables à une phrase musicale contenant
la perception de la même dimension émotive. Quatre-vingt-cinq participants
ont classé une sélection de musique émotionnelle et des vocalisations
prosodiques sur des échelles allant de « heureux » à « triste ». Les résultats
montrent de la cohérence et de l’exactitude dans les catégories d’émotions;
cependant il y a de plus grands écarts et une intensité plus faible dans les
exemples parlés parmi tous les participants et plus de cohérence dans les
exemples musicaux parmi les musiciens comparés aux non-musiciens. Cette
étude suggère que la prosodie de la parole peut communiquer le contenu
émotionnel d’une phrase sans éléments lexicaux et que les résultats sont
comparables, toutefois moins intenses que la même émotion transmise par la
musique. Cette étude a des implications pour le domaine delà musicothérapie
et ce par l’entremise de l'identification exacte de l'information affective
transmise, dans un stimulus non verbal.
Mots clés : musicothérapie, prosodie, émotion, langage, musique,
sémantique, dynamiques
Strong connections have been identified between music and language,
especially in relation to evolutionary background (Perlovsky, 2012], brain
connectivity (Koelsch, Gunter, Wittfoth, & Sammler, 2005], and skill transfer
(Besson, Chobert, &Marie, 2011], Some evolutionary theorists have suggested
the connection between music and language is in their communicative uses
(Cross, 2009; Juslin & Laukka, 2003], and a common communicative use
is emotional communication. It has been further suggested that language
is a more advanced form of emotional communication derived from music
(Mithen, 2009] and that both music and language derive from a pre-linguistic
system, which shared elements of music and language for communicative
purposes (Masataka, 2009], Such theoretical ideas combined with empirical
research on the topic (e.g., Johnansson, 2008; Levitin & Menon, 2003; Patel,
2008] show there are many shared similarities between music and language
in terms ofemotional communication. As emotional expression is considered
CanadianJournal ofMusic Therapy ooRevue canadienne de musicothérapie, 20(2), 87
paramount in communicating internal feelings and actions to others
(Scherer, 1995], and both music and language have been shown to effectively
communicate emotions (Steinbeis & Koelsch, 2008], it is useful to compare
the similarities and differences in how emotion is communicated through
both music and language. These connections will be explored throughout the
literature review.
Literature Review
Emotional Communication in Language and Music
Emotional communication in language and music is thought to be
related to the prosody of language (Pell, 2006], the dynamics of music (Van
der Zwaag, Westerlink, & Van den Broek, 2011], and how they effectively
convey meaning and emotion. Prosody in language is defined by intonation,
loudness, and tempo (Mitchell, Elliott, Barry, Cruttenden, &Woodruff, 2003]
and can be independent ofthe lexical elements ofspeech, defined as the word
and word-like elements oflanguage (Friederici, Meyer, &von Cramon, 2000].
The combination of semantic content and different combinations of prosodic
elements lead to emotional communication. The dynamic aspects of music,
which help to express emotion, are said to include but are not limited to
tempo, mode, harmony, tonality, pitch, rhythm, tension-resolution patterns,
and timing (Thompson, 2009], Different combinations ofprosodic or dynamic
information display differences in the type of emotion communicated both
in music and in language. Interestingly, neuroimaging studies have shown a
primary emotion pathway activated in response to both musical and spoken
emotional content as well as distinct networks activating different areas of
the right hemisphere of the brain (Steinbeis & Koelsch, 2008]. Music and
language also share processing pathways, and the processing of music and
language interact and affect each other in the brain (Fiveash & Pammer,
2014], The ability of both speech and music to communicate emotions has
been widely researched, and a growing body of evidence is pointing towards
strong connections between music and language, particularly in relation to
their respective emotional communication abilities.
Communicative Connections Between Music and Language
The extent of the connection between music and speech emotions can
be seen when looking at neuropsychological cases where impairment in one
domain affects performance in the other. While there are many processing
differences between music and speech (Zatorre &Baum, 2012; Zatorre, Belin,
& Penhune, 2002], there are also many similarities. For example, Nicholson,
Baum, Kilgour, Koh, Munhall, and Cuddy (2003] studied an amusic patient
who, following a right hemisphere stroke, was unable to detect differences
in music pitch and rhythm or recognize different melodies. After numerous
CanadianJournal ofMusic Therapy oo Revue canadienne de musicothérapie, 20(2), 88
tests they found that the patient’s pitch and rhythm recognition in speech
was similarly affected. He was unable to process intonation or discriminate
a question from a statement. He was, however, able to perceive speech in
other ways and carry on normally in most aspects of speaking life. Such a
phenomenon was also observed in two other amusic individuals, who
had similar issues with detecting intonation and rhythmic differences
across both speech and music stimuli (Patel, Peretz, Tramo, & Labreque,
1998). Such evidence from neuropsychology suggests elements of prosody
and musical dynamics are linked in the brain, and therefore theoretical
connections between musical dynamics and speech prosody are warranted.
Such connections have also been found in other areas ofresearch.
Further links between speech prosody and musical dynamics support
the existence of a connection between emotional communication in music
and in speech. Patel, Iversen, and Rosenberg (2006) looked at the differences
in instrumental music in England and France compared to the respective
prosody of English and French languages. They found that the composed
music had a number of similarities to the respective languages and that
the music reflected differences in prosodic speech. Such research suggests
language and music are mutually influential and share similar evolutionary
roots. Bowling, Sundararajan, Han, and Purves (2012) suggested there are
universal underpinnings of emotional communication in music dynamics
and speech prosody. They compared Western and Eastern (South Indian)
music and found similarities in tones used to express basic emotions as well
as similarities in emotional prosody within the different languages. This led
to the conclusion that universal prosodic and musical utterances exist across
cultures. Such evidence outlines the evolutionary basis for the connection
between music and speech prosody in terms ofemotive communication. This
can be seen more clearly when looking at transfer effects between music
training and emotional identification ofspeech prosody.
Musical Expertise and Emotional Identification in Speech
Correlations have also been found between musical expertise and a
higher ability to correctly identify emotional content in speech prosody (Lima
& Castro, 2011; Thompson, Schellenberg, & Husain, 2004). Such transfer
effects have been found in musically trained adults of different ages (Lima
&Castro, 2011; Thompson et al., 2004) as well as in children who have been
taking music lessons for only one year (Thompson et al., 2004), suggesting
cross-domain effects of practice between musical expertise and emotion
identification in speech. In addition to increased recognition of speech
prosody in unintelligible utterances, musicians have also been shown to
understand speech prosody in foreign languages better than non-musicians
(Thompson et al., 2004). Such transference has been linked to musicians’
Canadian Journal o f Music Therapy oo Revue canadienne de musicothérapie, 20(2'), 89
greater sensitivity to pitch sounds through training, which in turn influences
pitch sensitivity in language (Schôn, Magne, & Besson, 2004], Other theories
suggest musical training leads to enhanced emotional sensitivity and
emotional intelligence (Thompson, 2009), which facilitates a greater ability
to detect emotional expression in speech prosody (Trimmer &Cuddy, 2008).
Such transfer effects give strong support to the theory that music and speech
share similar emotional communication mechanisms, which has implications
in the practice of music therapy.
Music Therapy Implications
Therapeutically, the ability to convey and perceive emotions through
non-verbal means (whether through non-verbal utterances or instrumental
improvisation) is an incredibly important skill in working and communicating
with non-verbal, minimally verbal, and communicatively impaired clients
(Wigram, 2004). In practice, being aware of the emotive quality of vocal
and musical phrases allows clients and music therapists to communicate
emotions effectively without engaging in speech (Bruscia, 1998), which
may be difficult or impossible for some clients, as seen in those with stroke,
aphasia, and autism, for example. Awareness of emotional, behavioural, and
musical features can also aid the music therapist in empathie improvisation
(see Bruscia, 1987, for a description of Alvin’s methods) and in reacting to
the utterances of communicatively impaired clients. This influenced the
present study.
Purpose of the Study
The significant body of research suggesting connections between
musical dynamics and speech prosody in terms of emotional communication
led to the main research question of whether the same emotion can be
communicated through both music and speech prosody. When the lexical/
verbal elements of language are removed, the listener must rely on linguistic
prosody alone. Compared to the dynamics and melody within the music, it
was hypothesised that both music and speech prosody would convey similar
emotions. It was also hypothesized that musicians would be able to perceive
emotions in speech prosody better than non-musicians.
The proposed research questions aimed to investigate whether speech
prosody can accurately convey emotion, the extent to which the prosodic
speech ratings are comparable to ratings of emotional music, and the
differences in ratings between musicians and non-musicians.
CanadianJournal ofMusic Therapy co Revue canadienne de musicothérapie, 20(2), 90
Method
Participants
Eighty-five subjects with a mean age of 35.87 years (range = 15 to 72
years] participated in a survey comprising short audio clips of film music
and prosodic speech. Prior to beginning the survey, participants were asked
their age, native language (85% native English speakers], and other known
languages with self-reported level of fluency. They were then asked to rank
their musicianship using one of the following: non-musician (11%), musicloving
non-musician (41%), amateur musician (26%), semi-professional
musician (16%), or professional musician (6%). Participants followed a
public link on a social media site to access the survey and could withdraw
from the study at any time. Participants remained anonymous (identifying
characteristics, such as names and addresses were not collected) and did not
receive financial compensation for completion ofthe survey. Ethical approval
was granted from the University ofJyvàskylà, Finland, prior to data collection,
and participants gave written consent prior to participation.
Design
To test the hypothesis that participants would be able to identify
emotion at a similar level in both music and prosodic examples, six film music
excerpts (three happy and three sad) and six emotional speech excerpts
(three happy and three sad) were selected for the listening examples. The
musical excerpts were adapted from Eerola and Vouskoski’s (2011) study
on emotion in film music, and the emotional speech excerpts were adapted
from the Surrey Audio-Visual Expressed Emotion (SAVEE) database, which
contains recordings of voice actors reading lines of text in specific emotions
as rated by a test panel. Five of the music excerpts were reduced from full
score to a single midi instrument line using Finale NotePad software. The
sixth excerpt was a single-line piano melody that did not require further
reduction. Reductions retained the tempo, dynamics, solo instrumentation,
and articulation of the original pieces. The speech excerpts were re-recorded
by a voice actor deliberately muffling his voice to retain the prosody of the
phrases while obscuring their lexical elements. Excerpts were between
18 and 24 seconds long. The survey was designed using Qualtrics (www.
qualtrics.com) and was then distributed via social media networks.
Procedure
Participants were asked to rate each film music excerpt and each speech
excerpt on a Likert scale ofemotional intensity ranging from 1 for not at all to
5 for very in response to the questions "How happy did the audio sound?" and
"How sad did the audio sound?” Each excerpt was rated for both happiness
CanadianJournal ofMusic Therapy oo Revue canadienne de musicothérapie, 20(2), 91
and sadness. The music excerpts, besides the happy and sad ratings, had an
additional scale of 1 to 5 for familiarity. The excerpts were randomized and
participants were able to repeat them as needed. There was no time limit for
completion of the survey.
Results
To evaluate the happiness and sadness ratings of each condition (happy
music, happy vocals, sad music, sad vocals), the Likert scale ratings were
averaged and a final number for each condition was calculated. This resulted
in eight averaged responses.
A repeated measures one-way analysis of variance (ANOVA) was run to
see ifthere was a difference in responses between the eight groups. For coding
purposes, HM =happy music, HV- happy vocals, SM = sad music, and SV= sad
vocals. The results for the questions "How happy/sad did the audio sound?”
can be seen in Table 1, and are visualised in Figure 1. The ANOVAwas run with
a Greenhouse Geisser correction as sphericity was not assumed. The result of
the ANOVA was significant, F(7,84) = 156.9, p < .001. A bivariate correlation
was run to see whether familiarity scores were correlated with music ratings.
A significant positive correlation was found between happiness ratings on
happy music and familiarity scores, r = 0.31, p < .01. All other correlations
between familiarity and music ratings were non-significant.
TABLE 1
Mean and Standard Deviation Scores Across Conditions
Condition Mean Standard Deviation
HM (Happy) 3.55 0.69
SM (Happy) 1.70 0.65
HM (Sad) 2.09 0.59
SM (Sad) 3.94 0.81
HV (Happy) 3.05 1.06
SV (Happy) 2.04 0.83
HV (Sad) 2.13 0.85
SV (Sad) 2.64 0.99
Note: HM = happy music; SM = sad music; HV = happy vocals; SV = sad vocals. The
conditions Happy and Sad refer to the ratings of the question, "How happy/sad did
the audio sound?"
CanadianJournal ofMusic Therapy oo Revue canadienne de musicothérapie, 20(2), 92
■ H appiness Ratings i i Sadness Ratings
Figure 1. Graph of emotion rating (where 1= not at all; 2 - not very; 3 = somewhat;
4 = quite; 5= very) for stimuli type (HM = happy music; HV= happy vocals; SM = sad
music; SV= sad vocals) to the question, "How happy/sad did the audio sound?”Error
bars indicate one standard error either side of the mean.
To determine which differences between groups were significant,
post hoc tests using the Bonferroni correction were conducted. For coding
purposes, (happy) or (sad) refers to the happiness or sadness ratings of the
questions, "How happy/sad did the audio sound?” Pairwise comparisons
were made between the means of HM (happy) and HV(happy), HM (sad) and
HV (sad), SM (happy) and SV(happy), SM (sad) and SV(sad), SV(happy) and
HV (happy), SV (sad) and HV (sad), SM (happy) and HM (happy), SM (sad)
and HM (sad). All comparisons showed significant differences (p = 0.00)
except for the comparison of HM (sad) and HV (sad), which was p = 1.00.
Musical Ability
To assess whether the results differed depending on musical ability,
participants were grouped into those who rated themselves as a non-musician
(non-musician or music-loving non-musician; n =44) and those who rated
themselves as a musician (amateur musician, semi-professional musician,
or professional musician; n = 41). T-tests were run for the eight groups
compared above with a Bonferroni corrected alpha level of a. = a/n, making
the required significance level 0.05/8, = 0.006. Most comparisons remained
significant; however, for musicians the comparison between HM (happy) and
CanadianJournal ofMusic Therapy oo Revue canadienne de musicothérapie, 20(2), 93
HV (happy) was non-significant: t(40) = 2.527, p = .02. For non-musicians,
the comparison between SM (happy) and SV (happy) was non-significant,
t(43) = 1.547, p = .13. Figures 2 and 3 graph the difference in responses
between the four levels of rated musicianship and illustrate that sad music
was rated as more sad than sad vocals, whereas the difference between happy
music and happy vocals was not as profound but still apparent.
HM HV sm sv
Condition
Figure 2. Answers to the question, "How happy did the audio sound?" on a scale of 1
to 5, where 1= not at all and 5 =very, depending on whether the stimuli was happy
music (HM), happy vocals [HV], sad music (SM), or sad vocals (SV). Error bars
indicate one standard error either side of the mean.
CanadianJournal ofMusic Therapy ooRevue canadienne de musicothérapie, 20[2), 94
Condition
Figure 3. Answers to the question, "Howsad did the audio sound?" on a scale of 1 to 5,
where 1= not at all and 5 = very, depending on whether the stimuli was happy music
(HM), happy vocals (HV), sad music (SAT), or sad vocals (SK). Error bars indicate one
standard error either side of the mean.
Discussion
This study investigated the perceived emotional content of melodic and
speech prosodic phrases. Participants were presented with six single-line
musical excerpts and six prosodic phrases, three happy and three sad, and
were instructed to rate the happiness and sadness of each stimulus.
The initial results showed significant differences in the ratings across
music and vocal stimuli. While it was hypothesised that the music and
prosodic samples would convey similar levels of emotion and the samples
with the same intended emotion would not have significantly different
ratings, this only occurred for the happiness ratings of the sad music and
sad vocal stimuli. All other comparisons were significantly different in the
overall analysis. However, while results were not completely as hypothesised,
CanadianJournal ofMusic Therapy co Revue canadienne de musicothérapie, 20{2), 95
participants were able to discriminate intended emotions in both the music
and vocal prosody examples (though at different levels], indicating that both
vocal prosody without the lexical/verbal elements and musical excerpts can
effectively communicate emotion to varying degrees.
Significant differences between ratings of music and prosody with the
same intended emotion may be due to the nature of the tasks: participants
were not screened prior to the experiment and were able to control the stimuli
in terms of repetition, volume, and the equipment used to play the samples.
When separated into musician and non-musician categories, the results were
non-significant for happiness ratings across happy stimuli in musicians,
indicating that happy music and happy prosody were communicating
happiness at a similar level for musicians. In relation to the hypothesis, this
could suggest that musicians were better able to discriminate happiness in
the prosodic excerpts, perhaps due to greater pitch training. Sadness ratings
across happy stimuli in non-musicians were also non-significant. While nonmusicians
did not rate the intended emotion at similar levels, this result
shows that they were aware that the sad music and prosody examples were
not communicating happiness. This is encouraging in indicating that, across
all excerpts, happiness in both music and prosody was rated with little
variance, offering some support for the idea that music and prosody have
universally communicative potential (Bowling et al., 2012],
A notable difference was observed in the variance between the ratings
for music and prosody. Results indicated greater variance in the ratings for
vocal prosody compared to music, indicating a more consistent response to
music among participants. A possible reason for this could be the context
in which participants typically process musical and linguistic information.
Humans are generally exposed to music every day, whether intentionally,
as with consciously listening to a personal listening device or going to a
concert, or unintentionally, as with having a radio or television playing in the
background (North, Hargreaves, & Hargreaves, 2004). Music in everyday life
is strongly linked to emotional expression and perception (Juslin & Laukka,
2004], and this frequent exposure to music may prime us for perceiving
emotion during future exposure to different musical stimuli (Thompson,
2009],
Language, conversely, is most often coupled with lexical elements that
express, clearly, the speaker’s intentions (Cross et al., 2013]. Past studies
have found that incongruously paired speech-voice stimuli results in delayed
identification of the meaning of the stimulus (Ishii, Reyes, & Kitayama, 2003;
Kitayama & Ishii, 2002] and that prosody can affect visual tracking patterns
(Rigoulot &Pell, 2012]; however, little research exists on emotional accuracy
CanadianJournal ofMusic Therapy ooRevue canadienne de musicothérapie, 20(2], 96
ratings of speech prosody alone. It can be argued that, when removed
from a secondary source of emotional cueing (such as lexical speech, facial
expression, or gesture), prosody may be more difficult to classify than music,
as indicated by the variance observed. It is also possible that the prosodic
excerpts in this experiment, which were specific to the English language,
could have been difficult to rank for the participants who were not native
English speakers (15% in this study), or were bi- or multilingual, as it has
been shown to be easier to understand the prosody inherent in a person’s
native language (Pell & Skorup, 2008). Further research on emotional
perception in speech prosody could be conducted to investigate the role of
visual information in emotional identification of prosody as well as crosscultural
studies incorporating languages with differing prosodic patterns.
Another possibility to account for the variance between music and
prosody, as well as the intensity of the music ratings, may be found in the
structural elements of each stimulus. As per Mitchell et al. (2003), the
elements of linguistic prosody are intonation, loudness, and tempo, whereas
music also includes mode, pitch, tension, harmony, and other elements
(Thompson, 2009). Given the scope of music's dynamic elements and the
relative frequency with which music is used to communicate emotion
without the benefit of visual or lexical partnering, it would seem music is
more emotionally robust than language when the latter is reduced purely
to prosody. Greater consistency in results may have been observed with a
greater number of excerpts as well.
An interesting pattern is in the consistency in ratings of sad stimuli. No
significant discrepancies existed between participants for the sad prosodic
and musical stimuli, possibly indicating more universal communicability in
sadness. Furthermore, ratings for sad music were rated as more sad than
happy music was rated happy despite a positive correlation with familiarity
for happiness ratings in the happy music condition. This contradicts past
findings on emotional ratings of music with and without lyrics (Ali &
Peynircioglu, 2006) and may suggest an emotional memory-based influence
on the happy ratings of the happy music stimuli. This may also be due to the
original context and cultural specificity ofthe music. Film music is composed
with the intent to augment the atmosphere of a specific scenario and may be
more successful at expressing sadness when reduced to a single-line melody.
Further research using musical feature analysis software could be employed
to investigate this occurrence, as well as controlling the familiarity of the
musical stimuli.
CanadianJournal ofMusic Therapy oo Revue canadienne de musicothérapie, 20(2), 97
Implications for Music Therapy
The use and identification of emotional aspects of music and speech
are important in the delivery of music therapy, particularly with non-verbal
or communicatively impaired client populations. The ability to identify the
intended emotion in a non-verbal utterance or melody is a vital component in
a music therapist’s understanding of a client’s emotional state and music in
therapy. Similarly, being able to convey emotion allows the therapist to react
to, support, and communicate with that client. This study provides support
for the consistent accuracy in which individuals can correctly identify happy
and sad emotions in music and prosodic vocalisations (Bowling et al., 2012;
Steinbeis & Koelsch, 2008). This knowledge can be used by music therapists
to analyze emotional characteristics in a client’s instrumental music and
vocalization in session and in post-session analysis of musical and emotional
data. Future research incorporating additional basic emotions such as fear
and anger should be completed to expand what is known about the perception
of emotions in music and speech prosody.
Conclusion
Music and spoken language are both advanced cognitive processes that
convey emotion, whether through the intentions of the speaker, composer, or
musician or the perception of the listener. The aim of this experiment was to
investigate whether music and speech prosody could convey comparatively
similar emotions and whether the perception of emotions would be greater
in musicians compared to non-musicians. It was found that music and speech
prosody did appear to communicate the same emotions with some degree of
accuracy; the musicians showed greater statistical reliability in their ratings
of happiness across happy stimuli and the non-musicians greater statistical
reliability in their ratings ofhappiness across sad stimuli. The results indicated
stronger and less varied ratings ofmusic than speech prosody, possibly due to
music’s dynamic elements, with the highest degree of similarity in ratings of
sad stimuli. More research could be done incorporating additional emotions
and a greater number of excerpts to further enhance knowledge surrounding
music and prosody as related communicative processes.
Acknowledgements
We would like to acknowledge the support and contributions of Dr. GeoffLuck
and Dr. Stephen Croucher from the University of Jyvàskylâ, both of whom
encouraged us in this project and contributed valuable feedback throughout
the research and writing process.
We would also like to acknowledge the support ofthe University ofJyvàskylâ,
where this research was conducted.
CanadianJournal ofMusic Therapy ooRevue canadienne de musicothérapie, 20(2), 98
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