Perception of Nigerian Dùndún Talking Drum Performances as Speech-Like vs. Music-Like: The Role of Familiarity and Acoustic Cues

Abstract

It seems trivial to identify sound sequences as music or speech, particularly when the sequences come from different sound sources, such as an orchestra and a human voice. Can we also easily distinguish these categories when the sequence comes from the same sound source? On the basis of which acoustic features? We investigated these questions by examining listeners’ classification of sound sequences performed by an instrument intertwining both speech and music: the dùndún talking drum. The dùndún is commonly used in south-west Nigeria as a musical instrument but is also perfectly fit for linguistic usage in what has been described as speech surrogates in Africa. One hundred seven participants from diverse geographical locations (15 different mother tongues represented) took part in an online experiment. Fifty-one participants reported being familiar with the dùndún talking drum, 55% of those being speakers of Yorùbá. During the experiment, participants listened to 30 dùndún samples of about 7s long, performed either as music or Yorùbá speech surrogate (n = 15 each) by a professional musician, and were asked to classify each sample as music or speech-like. The classification task revealed the ability of the listeners to identify the samples as intended by the performer, particularly when they were familiar with the dùndún, though even unfamiliar participants performed above chance. A logistic regression predicting participants’ classification of the samples from several acoustic features confirmed the perceptual relevance of intensity, pitch, timbre, and timing measures and their interaction with listener familiarity. In all, this study provides empirical evidence supporting the discriminating role of acoustic features and the modulatory role of familiarity in teasing apart speech and music.

Vocal Imitation and Linguistic Processing of Super Mario Theme Music by Yorùbá Gamers

“…To a large extent, a Yorùbá speaker is aware when a drummer a switches from purely musical rhythm to speech-like rhythm and vice versa. This is established in the perceptual experiment of Durojaye et al (2021a). The logical move for future reseaarch is to compare the rhythm of Yorùbá speech and song to the rhythm of the (un)interpreted portions of the videogame music (as in Patel and Daniele, 2003).…”

“…Previous studies suggests that consumers of speech surrogates rely on pitch contour and context in their interpretation of the messages encoded with speech surrogates (Villepastour, 2010;Sotunsa, 2021), but the possibility of simply interpreting speech-surrogate messages based on previous experience and associated meaning cannot be ruled out. For example, the findings of Durojaye et al (2021a) indicates that familiarity with speech surrogacy plays a role in distinguishing speech mode from song mode. Though Durojaye et al (2021a) is about the categorisation of Yorùbá drum stimuli as music-like or speech-like, their finding is relevant to the interpretation of speech-surrogate messages.…”

“…For example, the findings of Durojaye et al (2021a) indicates that familiarity with speech surrogacy plays a role in distinguishing speech mode from song mode. Though Durojaye et al (2021a) is about the categorisation of Yorùbá drum stimuli as music-like or speech-like, their finding is relevant to the interpretation of speech-surrogate messages. In fact, the role of familiarity or previous experience in the interpretation of speech-surrogate codes is captured by the Yorùbá maxim which says, o r o so t i l¡ o ¡ n j¡ e o mo m ¡ i g¡ e n "if your child understands your code language, it is because you both share the secret" (Is .…”

Globally, songs and instrumental melodies are slower and higher and use more stable pitches than speech: A Registered Report

“…), it is challenging to analyze and compare key structural aspects such as pitch intervals, pitch contour shape, or note/syllable duration. While automatic segmentation can be effective for segmenting some musical instruments and animal songs (e.g., percussion instruments [Durojaye et al, 2021]; bird song notes separated by micro-breaths [Roeske et al 2020]), we found they did not provide satisfactory segmentation results compared to human manual annotation for the required task of segmenting continuous song/speech into discrete acoustic units such as notes or syllables (cf. Fig.…”

“…Although we can find studies showing higher brightness in singing performed by professional singers (Barnes et al, 2004;Merrill & Larrouy-Maestri, 2017;Sharma et al, 2021;Sundberg, 2001), our dataset does not necessarily consist of recordings by professional musicians and as in the case of Stone et al (1999) the prominent use of the high formant frequencies in singing may depend on musical style (but see Nikolsky et al, (2020) for the role of timbre played in personal music tradition). However, we would like to note that other aspects of timbre such as noisiness (spectral flatness) can potentially indicate the difference between song and speech (Durojaye et al, 2021).…”