Search Results (8)

By combining musicology, sound studies, and linguistics, this article goes beyond existing studies of voice and popular song to analyse vocal modifiers in four songs recorded by The Miracles in 1960 and 1967: ‘Way over there’ (1960), ‘Shop around’ (1960), ‘Who’s lovin’ you’ (1960) and ‘I second that emotion’ (1967). Vocal modifiers, a sub-category of paralanguage, are a nonverbal characteristic of speech that can alter meaning or convey emotion. By adopting a mixed methodology (spectral and music analysis alongside paralinguistics), I argue that aspects of The Miracles’ performative quality reside in their use of vocal modifiers, which occur in performance and are retained on recordings. Over time, specific uses, especially by the lead singer William “Smokey” Robinson, give rise to expressive tropes (significant or recurring themes, similar to a motive in Western art music). Expressive tropes are important for not only do they create aural connections across songs, they can also represent thematic content without the aid of lyrics and reveal subtle insights into non-lexical sounds that have long been acknowledged but have resisted analysis. Full article

Unique in mammals, the vocal generator of mysticete species comprises membranes covering the two arytenoid cartilages that vibrate as the airflow passes through the trachea from the lungs to the laryngeal sac. By adjusting the airflow as well as the spacing and orientation of the two cartilages, mysticetes control the vibrations and vary acoustic qualities of the produced sounds, including the duration, amplitude, and frequency modulation of vocalizations. Humpback whales control sound production in this way to construct a complex vocal repertoire, including vocalizations with or without harmonics as well as pulsed sounds. Some vocalizations within humpback whale songs, called units, exhibit non-linearities such as frequency jumps and chaos. Here, we further describe non-linear features of units, including two additional non-linearities: subharmonics and biphonation. Subharmonics within units are probably due to higher air flow rates and to the acoustic modes of internal resonators. Biphonic vocalizations are likely generated either by an asymmetric opening of the arytenoid cartilages or by the passage of the air flow at two separate positions along the membranes. Our analyses revealed acoustic non-linearities in vocalizations emitted by six different singers during multiple breeding seasons and from populations in different oceans, suggesting that singing humpback whales often produce units with non-linear features. Full article

The modulation of vocal elements, such as pitch, loudness, and duration, plays a crucial role in conveying both linguistic information and the speaker’s emotional state. While acoustic features like fundamental frequency (F0) variability have been widely studied in emotional speech analysis, accurately classifying emotion remains challenging due to the complex and dynamic nature of vocal expressions. Traditional analytical methods often oversimplify these dynamics, potentially overlooking intricate patterns indicative of specific emotions. This study examines the influences of emotion and temporal variation on dynamic F0 contours in the analytical framework, utilizing a dataset valuable for its diverse emotional expressions. However, the analysis is constrained by the limited variety of sentences employed, which may affect the generalizability of the findings to broader linguistic contexts. We utilized the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), focusing on eight distinct emotional states performed by 24 professional actors. Sonorant segments were extracted, and F0 measurements were converted into semitones relative to a 100 Hz baseline to standardize pitch variations. By employing Generalized Additive Mixed Models (GAMMs), we modeled non-linear trajectories of F0 contours over time, accounting for fixed effects (emotions) and random effects (individual speaker variability). Our analysis revealed that incorporating emotion-specific, non-linear time effects and individual speaker differences significantly improved the model’s explanatory power, ultimately explaining up to 66.5% of the variance in the F0. The inclusion of random smooths for time within speakers captured individual temporal modulation patterns, providing a more accurate representation of emotional speech dynamics. The results demonstrate that dynamic modeling of F0 contours using GAMMs enhances the accuracy of emotion classification in speech. This approach captures the nuanced pitch patterns associated with different emotions and accounts for individual variability among speakers. The findings contribute to a deeper understanding of the vocal expression of emotions and offer valuable insights for advancing speech emotion recognition systems. Full article

Many musicologists and researchers of popular music have recently stressed the omnipresence of covers in today’s music industry. In the sociolinguistics of music, however, studio-recorded covers and their potential differences from ‘original’ compositions have certainly been acknowledged in passing, but very few sociolinguists concerned with the study of song seem to have systematically explored how language use may differ in such re-imagined musical outputs. This article reports on a study which examines the language use of 45 blues artists from three distinct time periods (viz., 1960s, 1980s, and 2010s) and three specific social groups (viz., African American; non-African American, US-based; and non-African American, non-US based) distributed over 270 studio-recorded original and cover performances. Through gradient boosting decision tree classification, it aims to analyze the artists’ use of eight phonological and lexico-grammatical features that are traditionally associated with African American English (viz., /aɪ/ monophthongization, post-consonantal word-final /t/ deletion, post-consonantal word-final /d/ deletion, alveolar nasal /n/ in <ing> ultimas, post-vocalic word-final /r/ deletion, copula deletion, third-person singular <s> deletion, and not-contraction). Our analysis finds song type (i.e., the distinction between covers and originals) to have no meaningful impact on artists’ use of the examined features of African American English. Instead, our analysis reveals how performers seem to rely on these features to a great extent and do so markedly consistently, regardless of factors such as time period, socio-cultural background, or song type. This paper hence builds on our previous work on the language use of blues performers by further teasing out the complex indexical and iconic relationships between features of African American English, authenticity, and the blues genre in its various manifestations of time, place, and performance types. Full article

To understand the social interactions among songbirds, extracting the timing, position, and acoustic properties of their vocalizations is essential. We propose a framework for automatic and fine-scale extraction of spatial-spectral-temporal patterns of bird vocalizations in a densely populated environment. For this purpose, we used robot audition techniques to integrate information (i.e., the timing, direction of arrival, and separated sound of localized sources) from multiple microphone arrays (array of arrays) deployed in an environment, which is non-invasive. As a proof of concept of this framework, we examined the ability of the method to extract active vocalizations of multiple Zebra Finches in an outdoor mesh tent as a realistic situation in which they could fly and vocalize freely. We found that localization results of vocalizations reflected the arrangements of landmark spots in the environment such as nests or perches and some vocalizations were localized at non-landmark positions. We also classified their vocalizations as either songs or calls by using a simple method based on the tempo and length of the separated sounds, as an example of the use of the information obtained from the framework. Our proposed approach has great potential to understand their social interactions and the semantics or functions of their vocalizations considering the spatial relationships, although detailed understanding of the interaction would require analysis of more long-term recordings. Full article

Young territorial songbirds have calls to learn, especially calls that may be vital for maintaining territory. Territoriality is largely reinforced and communicated by vocal signals. In their natal territory, juvenile magpies (Gymnorhina tibicen) enjoy protection from predators for 8–9 months. It is not at all clear, however, when and how a young territorial songbird learns to distinguish the meaning of calls and songs expressed by parents, conspecifics, neighbours, and heterospecifics, or how territorial calls are incorporated into the juvenile’s own repertoire. This project investigated acquisition and expression of the vocal repertoire in juvenile magpies and assessed the responses of adults and juveniles to playbacks of neighbour and stranger calls inside their territory. The results reported here identify age of appearance of specific vocalisations and the limits of their expression in juveniles. One new and surprising result was that many types of adult vocalisation were not voiced by juveniles. Playbacks of calls of neighbours and strangers inside the natal territory further established that adults responded strongly but differentially to neighbours versus strangers. By contrast, juveniles needed months before paying any attention to and distinguishing between neighbour and stranger calls and eventually did so only in non-vocal ways (such as referral to adults). These results provide evidence that auditory perception not only includes recognition and memory of neighbour calls but also an assessment of the importance of such calls in the context of territoriality. Full article

The vocalization behavior of humpback whales was monitored over vast areas of the Gulf of Maine using the passive ocean acoustic waveguide remote sensing technique (POAWRS) over multiple diel cycles in Fall 2006. The humpback vocalizations comprised of both song and non-song are analyzed. The song vocalizations, composed of highly structured and repeatable set of phrases, are characterized by inter-pulse intervals of 3.5 ± 1.8 s. Songs were detected throughout the diel cycle, occuring roughly 40% during the day and 60% during the night. The humpback non-song vocalizations, dominated by shorter duration (≤3 s) downsweep and bow-shaped moans, as well as a small fraction of longer duration (∼5 s) cries, have significantly larger mean and more variable inter-pulse intervals of 14.2 ± 11 s. The non-song vocalizations were detected at night with negligible detections during the day, implying they probably function as nighttime communication signals. The humpback song and non-song vocalizations are separately localized using the moving array triangulation and array invariant techniques. The humpback song and non-song moan calls are both consistently localized to a dense area on northeastern Georges Bank and a less dense region extended from Franklin Basin to the Great South Channel. Humpback cries occur exclusively on northeastern Georges Bank and during nights with coincident dense Atlantic herring shoaling populations, implying the cries are feeding-related. Full article

Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks. Full article