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Shared Acoustic Codes Underlie Emotional Communication in Music and Speech - Evidence from Deep Transfer Learning (Datasets)
<p>This repository contains the datasets used in the article "Shared Acoustic Codes Underlie Emotional Communication in Music and Speech - Evidence from Deep Transfer Learning" (Coutinho & Schuller, 2017). </p> <p>In that article four different data sets were used: SEMAINE, RECOLA, ME14 and MP (acronyms and datasets described below). The SEMAINE (speech) and ME14 (music) corpora were used for the unsupervised training of the Denoising Auto-encoders (domain adaptation stage) - only the audio features extracted from the audio files in these corpora were used and are provided in this repository. The RECOLA (speech) and MP (music) corpora were used for the supervised training phase - both the audio features extracted from the audio files and the Arousal and Valence annotations were used. In this repository, we provide the audio features extracted from the audio files for both corpora, and Arousal and Valence annotations for some of the music datasets (those that the author of this repository is the data curator).</p> <p>Below, you can find description of the various corpora, the details about the data stored in this repository and information on how to obtain the rest of the data used by Coutinho and Schuller (2017).</p> <p><strong>SEMAINE (speech)</strong></p> <p>The SEMAINE corpus (McKeown, Valstar, Cowie, Pantic & Schroder, 2012) was developed specifically to address the task of achieving emotion-rich interactions, and it is adequate for this task as it comprises a wide range of emotional speech. It includes video and speech recordings of spontaneous interactions between human and emotionally stereotyped `characters'. Coutinho & Schuller (2017) used a subset of this database (called <em>Solid-SAL</em>). The <em>Solid-SAL</em> dataset is freely available for scientific research purposes (see http://semaine-db.eu). This repository includes the audio features used in Coutinho & Schuller (2017) (under features/SEMAINE).</p> <p><strong>RECOLA (speech)</strong></p> <p>The RECOLA database (Ringeval, Sonderegger, Sauer & Lalanne, 2013) consists of multimodal recordings (audio, video, and peripheral physiological activity) of spontaneous dyadic interactions between French adults. Coutinho & Schuller (2017) used the RECOLA-Audio module which consists of the audio recordings of each participant in the dyadic phase of the task. In particular, they used the non-segmented high-quality audio signals (WAV format, 44.1kHz, 16bits), obtained through unidirectional headset microphones, of the first five minutes of each interaction. Annotations consist of time-continuous ratings of the level of Arousal and Valence dimensions of emotion perceived by each rater while seeing and listening the audio-visual recordings of each participant task. The publicly available annotated dataset includes only part of the data which amounts to a total number of 23 instances. The time frame length used by Coutinho & Schuller (2017) is 1s (the original annotations were downsampled). This repository includes the audio features used in Coutinho & Schuller (2017) (under features/RECOLA). To obtain the annotations you should contact the author of the original study (see https://diuf.unifr.ch/diva/recola/download.html for further details).</p> <p><strong>ME14 (music)</strong></p> <p>The MediaEval ``Emotion in Music'' task is dedicated to the estimation of Arousal and Valence scores continuously in time and value for song excerpts from the Free Music Archive. Coutinho and Schuller (2017) used the whole corpus (development and test sets for the 2014 challenge) which includes 1,744 songs belonging to 11 musical styles -- Soul, Blues, Electronic, Rock, Classical, Hip-Hop, International, Folk, Jazz, Country, and Pop (maximum of five songs per artist). This repository includes the audio features used in Coutinho & Schuller (2017) (under features/ME14). The full dataset (including annotations) can be obtained from http://www.multimediaeval.org/mediaeval2014/emotion2014/.</p> <p><strong>MP (music)</strong></p> <p>This is a corpus compiled specifically for this work described in Coutinho & Schuller (2017) using data collected in four previous studies. It consists of emotionally diverse full music pieces from a variety of musical styles (Classical and contemporary Western Art, Baroque, Bossa Nova, Rock, Pop, Heavy Metal, and Film Music). Annotations were obtained in controlled laboratory experiments whereby the emotional character of each piece was evaluated time-continuously in terms of levels of Arousal and Valence perceived by listeners (ranging between 35 to 52 in the four studies). In what follows, some details about the various studies are described.</p> <ul> <li>MP<sub>DB1</sub>: This subset of the MP corpus consists of the data reported by Korhonen (2004), and gently made available by the author. This dataset includes six full (or long excerpts) music pieces ranging from 151s to 315s in length (only classical music). Each piece was annotated by 35 participants (14 females). The time series correspondents to each music piece were collected at 1Hz. The golden standard for each piece was computed by averaging the individual time series across all raters. This repository includes the audio features used in Coutinho & Schuller (2017) (under features/MP/DB1). To obtain the labels please contact the author of the original study.</li> <li>MP<sub>DB2</sub>: The dataset by Coutinho & Cangelosi (2011) includes 9 full pieces (43s to 240s long) of classical music (romantic repertoire) annotated by 39 subjects (19 females). Values were recorded every time the mouse was moved with a precision of 1 ms. The resultant timeseries were then resampled (moving average) to a synchronous rate of 1 Hz. The golden standard for each piece was computed by averaging the individual time series across all raters. This repository includes the audio features (under features/MP/DB2) and labels (under annotations/MP/DB2) used in Coutinho & Schuller (2017).</li> <li>MP<sub>DB3</sub>: This dataset was collected by Coutinho & Dibben (2012) and it consists of 8 pieces of film music (84s to 130s long) taken from the late 20th century Hollywood film repertoire. Emotion ratings were given by 52 participants (26 females). The annotation procedure, data processing, and golden standard calculations were identical to MP<sub>DB2</sub>. This repository includes the audio features (under features/MP/DB3) and labels (under annotations/MP/DB3) used in Coutinho & Schuller (2017).</li> <li>MP<sub>DB4</sub>: This dataset was collected by Grewe, Nagel, Kopiez and Altenmüller (2007), and gently made available by the authors. It includes seven music pieces (127s to 502s in length) of heterogeneous styles (e.g., Rock, Pop, Heavy Metal, Classical). Each music piece was annotated by 38 participants (29 females) using an identical methodology to MP<sub>DB2</sub> and MP<sub>DB3</sub>. Data processing and golden standard calculations were also identical. This repository includes the audio features (under features/MP/DB4) used in Coutinho & Schuller (2017). To obtain the labels contact the authors of the original study</li> </ul> <p> </p> <p><strong>Bibliography</strong></p> <p>Coutinho, E., & Cangelosi, A. (2011). Musical emotions: predicting second-by-second subjective feelings of emotion from low-level psychoacoustic features and physiological measurements. <em>Emotion</em>, <em>11</em>(4), 921.</p> <p>Coutinho, E., & Dibben, N. (2013). Psychoacoustic cues to emotion in speech prosody and music. <em>Cognition & Emotion</em>, <em>27</em>(4), 658-684.</p> <p>Coutinho E, Schuller B (2017) Shared acoustic codes underlie emotional communication in music and speech—Evidence from deep transfer learning. PLoS ONE 12(6): e0179289. https://doi. org/10.1371/journal.pone.0179289.</p> <p>Grewe, O., Nagel, F., Kopiez, R., Altenmüller, E. (2007). Emotions over time: synchronicity and development of subjective, physiological, and facial affective reactions to music. <em>Emotion, 7</em>(4), pp. 774-788. DOI: 10.1037/1528-3542.7.4.774.</p> <p>Korhonen, M. (2004). Modeling Continuous Emotional Appraisals of Music Using System Identification. Available from: http://hdl.handle.net/10012/879.</p> <p>McKeown, G., Valstar, M., Cowie, R., Pantic, M., Schroder, M. (2012). The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent. <em>IEEE Transactions on Affective Computing</em>, 3, pp. 5-17. DOI: http://doi.ieeecomputersociety.org/10.1109/T-AFFC.2011.20.</p> <p>Ringeval, F., Sonderegger, A., Sauer, J. & Lalanne, D. (2013). Introducing the RECOLA Multimodal Corpus of Remote Collaborative and Affective Interactions. In <em>Proceedings of the 2nd International Workshop on Emotion Representation, Analysis and Synthesis in Continuous Time and Space (EmoSPACE 2013)</em>, Shanghai, China. IEEE</p>
Data for: Collective signalling is shaped by feedbacks between signaller variation, receiver perception, and acoustic environment in a simulated communication network
<p>Communication takes place within a network of multiple signallers and receivers. Social network analysis provides tools to quantify how an individual's social positioning affects group dynamics, and the subsequent biological consequences. However, network analysis is rarely applied to animal communication, likely due to the logistical difficulties of monitoring natural communication networks. We generated a simulated communication network to investigate how variation in individual communication behaviours generates network effects, and how this communication network's structure feeds back to affect future signalling interactions. We simulated competitive acoustic signalling interactions among chorusing individuals and varied several parameters related to communication and chorus size to examine their effects on calling output and social connections. Larger choruses had higher noise levels, and this reduced network density and altered the relationships between individual traits and communication network position. Hearing sensitivity interacted with chorus size to affect both individuals' positions in the network and the acoustic output of the chorus. Physical proximity to competitors influenced signalling, but a distinctive communication network structure emerged when signal active space was limited. Our model raises novel predictions about communication networks that could be tested experimentally, and identifies aspects of information processing in complex environments that remain to be investigated. </p>
Figure 1-2 in Acoustic communication in two species of the Hypsiboas albopunctatus group (Anura: Hylidae) in sympatry and allopatry
Figure 1-2. Advertisement (1) and aggressive (2) calls of Hypsiboas abopunctatus from Barro Alto, Goiás, Brazil. Above audiospectrogram, below oscillogram. (1) Air temperature = 23.4°C, Air humidity = 68%, SVL = 51,84 mm; (2) Air temperature = 19,8°C; Air humidity = 88%; SVL = 50,27 mm.
Figure 3-5 in Acoustic communication in two species of the Hypsiboas albopunctatus group (Anura: Hylidae) in sympatry and allopatry
Figure 3-5. Advertisement (3), aggressive I (4) and aggressive II (5) calls of Hypsiboas paranaiba from Barro Alto, Goiás, Brazil. Above audiospectrogram; below oscillogram. (3) Air temperature = 21°C, Air humidity = 92%, SVL = 45.03 mm; (4) Air temperature = 21°C, Air humidity = 92%, SVL = 45.04 mm; (5) Air temperature = 21°C, Air humidity = 92%, SVL = 43.22 mm.
Data for: Collective signalling is shaped by feedbacks between signaller variation, receiver perception, and acoustic environment in a simulated communication network
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Supporting data: Functional plasticity of the swim bladder as an acoustic organ for communication in a vocal fish
<div> <p>In this study, we show that the swim bladder of male plainfin midshipman fish (<em>Porichthys notatus</em>) exhibits reproductive state-dependent changes in morphology and function for sound production and reception. We quantified swim bladder morphometrics and utilized psuedolandmarking to identify differences in nonreproductive and reproductive male swim bladders. We utilized auditory evoked potential recordings, to measure the auditory sensitivity of saccular hair cells in response to sound pressure levels ranging from 97 - 154 dB re: 1 µPa to determine how the swim bladder contributes to midshipman auditory sensitivity. Finally, we used finite element modeling to explore the frequency response of nonreproductive and reproductive male swim bladders.</p> </div>
Distribution, response to human disturbance, habitat preferences, and acoustic communication of tree hyraxes of Mt. Kilimanjaro, Tanzania
<p><span>This data consists data from recordings done in Mt. Kilimanjaro. Hourly calls of tree hyraxes have been calculated between 19.00 until 06:00. Dataset also has variables collected by other research groups.</span></p> <p><span>We combined our data of cue count per hour with data to analyse tree hyrax density with explanatory variables to model occupancy of tree hyraxes in Kilimanjaro. Dataset was combined from several research projects conducted within the Kili-Project (Hemp et al. 2018) (Table 1). Variables included forest type, temperature (Appelhans et al. 2015) precipitation (Appelhans et al. 2016). diameter breast height (DBH), leaf density, max vegetation height, and leaf area index (LAI) (Rutten et al., 2015). We also included land use index (LUI) (Peters et al. 2019) to the dataset, which included four different variables (percentage plant biomass removal, agricultural inputs, modification of the vegetation and percentage of agricultural area in the surroundings). </span></p> <p><span>Abstract</span></p> <p><span>Limited knowledge exists of the distribution, habitat selection, behavior and response to human disturbance of many mammalian species from mountains of Africa. This is especially true for nocturnal mammals. We studied acoustically very active tree hyraxes (<em>Dendrohyrax validus validus</em>) from Mt. Kilimanjaro National Park, Tanzania mainly with bioacoustical methods. To gain understanding of the habitat preferences of tree hyraxes we combined bioacoustical data with botanical and meteorological data collected earlier by <span>KiLi Project</span>. According to GLMM analysis, disturbance caused by logging or forest fires significantly reduced tree hyrax calling activity. In Mt. Kilimanjaro, highest density of tree hyraxes was found from 2750 m a.s.l. It seems that extensive hunting in the past and selective logging below elevation 2500 m caused tree hyraxes to move up the mountain. Calls of tree hyraxes in Mt. Kilimanjaro resemble calls emitted by hyraxes in Taita Hills, Kenya; however, there are clear differences in their calling cultures. In Mt. Kilimanjaro tree hyraxes also sing songs, and their acoustic communication is very active and diverse. In most preferred habitats, groups of tree hyraxes may call 4500–5500 times during one night. Calling seem to have elements of turn taking and individual signatures. Future of tree hyraxes in large, 650 km<sup>2</sup>, Mt. Kilimanjaro National Park seems promising and perhaps in the future tree hyraxes will recolonize the whole park area again.</span></p>
Data from: Phenotypic integration and the evolution of signal repertoires: a case study of treefrog acoustic communication
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Supporting data: Functional plasticity of the swim bladder as an acoustic organ for communication in a vocal fish
Open the record for dataset details and reuse information.
Fig. 4 in Acoustic communication in the Lusitanian toadfish, Halobatrachus didactylus: evidence for an unusual large vocal repertoire
Fig. 4. Long grunt trains (LGT) were significantly longer (A), were made up of more grunts (B), but had similar grunt periods (C) than grunt trains (GT). Grunts in LGT had similar duration (D) and dominant frequency (F), but had a higher number of pulses (E) than grunts in GT. Medians and quartiles are depicted. Mann–Whitney tests,, P, 0.001;, P, 0.01.
Fig. 3 in Acoustic communication in the Lusitanian toadfish, Halobatrachus didactylus: evidence for an unusual large vocal repertoire
Fig. 3. During the present study, nesting Lusitanian toadfish males emitted sounds that have not previously been described such as triple croaks (A), long grunt trains (B) and combinations of long grunt trains with other sound types (C). In (C) a long grunt train (thin line) combines with a grunt train (double line) that ends in a croak (thick line), which blends into a boatwhistle (dashed line), which is then followed by another long grunt train (thin line). Note that in (C), the LGT is hardly visible in the oscillogram due its much lower amplitude than the other sounds. Sonograms used a 30 Hz filter bandwidth.
Fig. 2 in Acoustic communication in the Lusitanian toadfish, Halobatrachus didactylus: evidence for an unusual large vocal repertoire
Fig. 2. Mean percentage of the different sound types emitted per hour by 16 nesting males during one week in the peak of the breeding season.
Diversification of a polyploid complex: the biogeography and acoustic communication evolution of North American gray treefrogs throughout the Quaternary
<p>Polyploid speciation and whole genome duplications are major drivers of biological diversity. After polyploid species are formed, the interactions between diploid and polyploid lineages may generate additional diversity in novel cytotypes and phenotypes. In anurans, mate choice by acoustic communication is the primary method by which individuals identify their own species and assess suitable mates. As such, the evolution of acoustic signals is an important mechanism for contributing to reproductive isolation and diversification in this group. The North American gray treefrog complex, consisting of the diploid Hyla chrysoscelis and the tetraploid Hyla versicolor, has long been used to study reproductive isolation and research on this system has consistently driven this field forward. Here, we estimate the biogeographic history of this group, focusing specifically on the geographic origin of whole genome duplication and the expansion of lineages out of refugia following climate oscillations and retreats of the Laurentide ice sheet. We then test for lineage-specific differences in mating signals by applying comparative methods to a large acoustic data set collected over 52 years that includes >1500 individual frogs. Finally, we expand upon our results in light of recent estimates of the complex's genomic evolution to describe the history of diversification in gray treefrogs throughout the Quaternary.</p>
Fig. 11 in Hyperdiverse songs, duetting, and the roles of intra- and intersexual selection in the acoustic communication of the genus Eurycorypha (Orthoptera: Tettigonioidea, Phaneropterinae)
Fig. 11 Oscillograms of song interactions in Eurycorypha pseudovaria. a–e Male-female duets, details. f Male-male interaction (1.5 s sections). See text and discussion for details
Fig. 7 Eurycorypha conclusa. a in Hyperdiverse songs, duetting, and the roles of intra- and intersexual selection in the acoustic communication of the genus Eurycorypha (Orthoptera: Tettigonioidea, Phaneropterinae)
Fig. 7 Eurycorypha conclusa. a Overview of a series of long echemes in male song (40 s section). b, f Male-female duets, details
Fig. 3 in Hyperdiverse songs, duetting, and the roles of intra- and intersexual selection in the acoustic communication of the genus Eurycorypha (Orthoptera: Tettigonioidea, Phaneropterinae)
Fig. 3 Power spectra of male calling song of Eurycorypha species. In species with restricted frequency range, short black lines mark its end. Blue lines indicate power spectra of female responses
Fig. 10 in Hyperdiverse songs, duetting, and the roles of intra- and intersexual selection in the acoustic communication of the genus Eurycorypha (Orthoptera: Tettigonioidea, Phaneropterinae)
Fig. 10 Oscillograms of song interactions in Eurycorypha pianofortis. a Male song demonstrating the transition between two echeme types. b Male-female duet
Fig. 2 in Hyperdiverse songs, duetting, and the roles of intra- and intersexual selection in the acoustic communication of the genus Eurycorypha (Orthoptera: Tettigonioidea, Phaneropterinae)
Fig. 2 Tegmina and structures used for sound production in Eurycorypha curviflava. a Male and b female tegmina. Base of left and right tegmen (dorsal field) in c male (left tegmen shown from lower side, stridulatory file visible, mirror image) and d female. e Male stridulatory file on lower side of left tegmen. f Female stridulatory files on upper side of right tegmen. Scale, a, b 10 mm and c, d, e, f 1 mm
Fig. 9 in Hyperdiverse songs, duetting, and the roles of intra- and intersexual selection in the acoustic communication of the genus Eurycorypha (Orthoptera: Tettigonioidea, Phaneropterinae)
Fig. 9 Oscillograms of song interactions in Eurycorypha curviflava and E. ligata. a Male-female duet in E. curviflava, b, c Male-male interactions in E. ligata (6 s sections)
Fig. 8 in Hyperdiverse songs, duetting, and the roles of intra- and intersexual selection in the acoustic communication of the genus Eurycorypha (Orthoptera: Tettigonioidea, Phaneropterinae)
Fig. 8 Oscillograms of long acoustical (1 min sections) interactions of a males in Eurycorypha curviflava and duets of males and females in b E. ligata, c E. pianofortis, and d E. pseudovaria
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Allen Brain Atlas
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.