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503 results for “Voice”
FIGURE 1 in A new " Bat-Voiced " species of Dendropsophus Fitzinger, 1843 (Anura, Hylidae) from the Amazon Basin, Brazil
FIGURE 1. Distribution of Dendropsophus ozzyi sp. nov. (A) Amazon region (B) a close-up of the Rio Madeira–Rio Tapajós interfluve evidencing known occurrence of the new species in the States of Amazonas and Pará. Star (type locality) = Comunidade Bragança, Rio Paraconi, Floresta Nacional de Pau-Rosa (FNPR), Maués, Amazonas, Brazil. Circle = Igarapé Prudente, Juruti, State of Pará, Brazil. Square = Igarapé Mutum, Juruti, State of Pará, Brazil.
FIGURE 6 in A new " Bat-Voiced " species of Dendropsophus Fitzinger, 1843 (Anura, Hylidae) from the Amazon Basin, Brazil
FIGURE 6. Dorsal (a) and ventral (b) color patterns of 21 preserved paratypes of Dendropsophus ozzyi sp. nov. from Juruti, Pará, Brazil. Scale bar = 20.0 mm. (1) INPA-H 32746; (2) INPA-H 32747; (3) INPA-H 32743; (4) MZUSP 154084; (5) MZUSP 154085; (6) MZUSP 154086; (7) MZUSP 154087; (8) MZUSP 154088; (9) INPA-H 32744; (10) INPA-H 32745; (11) INPA-H 32742; (12) INPA-H 32748; (13) CFBH 35760; (14) MNRJ 86921; (15) MNRJ 86925; (16) CFBH 35763; (17) CFBH 35764; (18) CFBH 357602; (19) MNRJ 86922; (20) MNRJ 86923; (21) MNRJ 86924. For additional information see Table 1 and text.
Voices, instruments and somewhere in between: using musical medium to cross the knowledge organization/music boundary
<p>This paper considers the boundary between the library and information science (LIS) specialist and the music specialist's approach to music classification, and shows how crossing this boundary enhances knowledge on both sides. Musical medium – in other words, the forces needed to rehearse or perform a musical work – is at the heart of music classification. Therefore, three examples of music medium phenomena will be considered from a combined LIS/music perspective. </p><p>First, the "great" vocal/instrumental divide will be considered. The paper will explore how this fundamental musicological categorization is reflected in LIS classification schemes, and what happens when the categorization of a vocal/instrumental hybrid such as the choral symphony is attempted. The paper then considers the classification of musical instruments, comparing taxonomies within organology – the study of musical instruments – to LIS classification schemes for music. Part of this analysis will consider the categorization of instruments into "families", and how this differs between the music and LIS disciplines. This will be followed by an examination of the cross-fertilization between organology classification schemes and their bibliographic cousins, including an account of how the major organological taxonomy "Hornbostel and Sachs" crossed through the music boundary and into LIS territory. </p><p>Through exploring these three specific examples of issues in classifying music medium, the general relationship between the LIS and music disciplines can be examined. The paper will reveal that this relationship takes on many different guises, and that crossing the LIS/music boundary – in both directions – is critical to understanding the fundamental elements of music classification.</p>
Database of Basque voice constructions (16th-21st centuries)
<p>Database of Basque voice constructions (16th-21st centuries)</p>
FIGURE 2 in Integrating voice and phenotype in a revision of the brush cuckoo Cacomantis variolosus (Aves: Cuculidae) complex
FIGURE 2. The seven element shapes found in the Cacomantis variolosus complex. Taxon names given represent the following geographic song types (see Results): sepulcralis—Sundaland and Philippines, virescens—Sulawesi and Sula, aeruginosus—resident Moluccas, variolosus—Australasia, blandus—Admiralty Islands, addendus—Solomon Islands.
FIGURE 4 in Integrating voice and phenotype in a revision of the brush cuckoo Cacomantis variolosus (Aves: Cuculidae) complex
FIGURE 4. Boxplots of vocal measurements. Explanation of variables: pacing—elements per second; element duration in seconds; changes in center frequency in Hertz. For further explanation of vocal parameters, see Methods.
FIGURE 3 in Integrating voice and phenotype in a revision of the brush cuckoo Cacomantis variolosus (Aves: Cuculidae) complex
FIGURE 3. Principal component analysis plot based on the four vocal parameters measured. The first principal component (PC1) chiefly differentiates addendus and virescens, while the second PC splits the sepulcralis group and variolosus group. The inferred Australian migrant variolosus individual (ML 168559) found on Flores, Nusa Tenggara, Indonesia, is denoted by an arrow.
FIGURE 1 in Integrating voice and phenotype in a revision of the brush cuckoo Cacomantis variolosus (Aves: Cuculidae) complex
FIGURE 1. Distribution of the Cacomantis variolosus complex across the Indo-Pacific region: (a) showing the ranges of taxa listed in Table 1; (b) showing all species and subspecies recognized as a result of this study, with species encircled.
Amharic Voice Commands
<p>This dataset contains voice commands that are recorded in the Amharic language</p>
FIGURE 6 in Taxonomic status of Parotia berlepschi Kleinschmidt, 1897 based on analysis of external appearance, voice and behavior (Aves: Paradisaeidae)
FIGURE 6. Two courtship behaviors documented in P. berlepschi: (A) horizontal perch pivot, which involves the male adopting a rigid horizontal body posture, head and tail held up and flank plumes flared outward from the body so that the white portions form two semi-circular 'disks' that emanate from either side of the body while the body is pivoted side-to-side in a way that accentuates the white plumes; (B) leaf presentation, which is a modifier display that involves holding a yellow or light colored leaf in the bill while performing other displays. Derived from photos ML 48065351 and 48068531.
FIGURE 5 in Taxonomic status of Parotia berlepschi Kleinschmidt, 1897 based on analysis of external appearance, voice and behavior (Aves: Paradisaeidae)
FIGURE 5. Spectrograms of advertisement vocalizations of P. berlepschi (A, B) compared with those from two geographically varying populations within the P. carolae group (C, D). P. berlepschi has two primary advertisement vocalizations: (A) a shrill two-note form reminiscent of a squeaky toy and (B) a shrill four-note, slightly ascending whinny. In comparison, P. carolae from Mt. Stolle (C) gives a powerfully whistled three-note advertisement vocalization, and P. carolae from Crater Mountain (D) gives a single frantic quavering whistle-note. Spectrograms C and D are modified from Scholes (2006).
FIGURE 3 in Taxonomic status of Parotia berlepschi Kleinschmidt, 1897 based on analysis of external appearance, voice and behavior (Aves: Paradisaeidae)
FIGURE 3. Forehead, facial, and crown appearance of P. berlepschi specimen MZB 30.666 (A–C) compared to P. carolae specimen AMNH 302376. Notable characters differentiating P. berlepschi from P. carolae include the all black loral feathering on the frontal crest of P. berlepschi (A, C) versus the extensively white-tipped loral feathering of P. carolae (D, F); the narrow coppery-bronze stripe from above the eye to the crown of P. berlepschi (A) versus the more extensive, crescent shaped, coppery facial markings in front of the eye of P. carolae; the darker malar, cheek and throat, including the "whiskers" of P. berlepschi (B) compared to the straw-colored appearance of the same feathering in P. carolae (D, E). Note the appearance of the frontal crest in the "open" position (C, F).
FIGURE 4 in Taxonomic status of Parotia berlepschi Kleinschmidt, 1897 based on analysis of external appearance, voice and behavior (Aves: Paradisaeidae)
FIGURE 4. Female facial markings and eye color of (A) P. berlepschi and (B) P. carolae. The forehead of P. berlepschi has more extensive white in the middle, which extends almost to the fore-crown; the brown loral patch is also more extensive with less white near the base of the upper mandible; and the supercilium extends further back onto the nape and is whiter than in P. carolae. Eye color of female-plumaged P. berlepschi is pale grey-blue (A) versus yellow in P. carolae (B). Note: the difference in tint between the two photos is largely due to differing white balance and flash settings, which make the plumage of the P. carolae image look more "warm" (orange) than the P. berlepschi image which is shifted slightly toward the "cooler" (blue) end. Image (A) is of a bird in the hand taken by BB. Image (B) is modified from photo ML 48068781.
FIGURE 2 in Taxonomic status of Parotia berlepschi Kleinschmidt, 1897 based on analysis of external appearance, voice and behavior (Aves: Paradisaeidae)
FIGURE 2. Forehead, facial, crown and nape appearance of living P. berlepschi (A–D) as compared to living P. carolae (E–H). Notable characters that differentiate P. berlepschi from P. carolae include the all-black loral feathering on the frontal crest of P. berlepschi (A–C) versus the extensively white-tipped loral feathering of P. carolae (E–H); the eye-to-crown "tiara" of P. berlepschi (B, C) versus the more extensive coppery facial markings in front of and surrounding the eye of P. carolae; the darker malar, cheek and throat of P. berlepschi (A, B) versus the much lighter straw colored appearance of P. carolae (F); the almost nonexistent coppery-bronze hind crown patch of P. berlepschi (C) versus the extensive one visible at all times on the crown of P. carolae (G); the grey-blue eye color of P. berlepschi (A, B) versus the bright lemon yellow of P. carolae (E, F) and the rich bronzy sheen on the nape and upper mantle of P. berlepschi (D) compared to the black nape of P. carolae (H). Plates derived from photos ML 48065581 (A), 48065591 (B), 48065601 (C), 48065621 (D), 48068971 (E), 48068791 (F), 48068861 (G) and 48152301 (H).
FIGURE 1 in Taxonomic status of Parotia berlepschi Kleinschmidt, 1897 based on analysis of external appearance, voice and behavior (Aves: Paradisaeidae)
FIGURE 1. Parotia-specific plumage ornaments referenced herein: (A) frontal crest, (A1) loral tufts, (A2) supranarial tufts and (A3) forehead tufts, (B) crown patch, (C) throat "whiskers", and (D) mantle cape. Modified from Scholes (2006), which was modified from Frith & Beehler (1998) and Schodde & McKean (1973).
Expert annotations for the Catalan Common Voice (v13)
<h2>Dataset Description</h2> <p>- Homepage: <a href="https://projecteaina.cat/tech/">https://projecteaina.cat/tech/</a>]<br>- Point of Contact: langech@bsc.es</p> <h3>Dataset Summary</h3> <p>These are the annotations made by a team of experts on the speakers with more than 1200 seconds recorded in the Catalan set of the <a href="https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0/tree/main/transcript/ca">Common Voice dataset (v13)</a>.</p> <p>The annotators were initially tasked with evaluating all recordings associated with the same individual. Following that, they were instructed to annotate the speaker's accent, gender, and the overall quality of the recordings.</p> <p>The accents and genders taken into account are the ones used until version 8 of the Common Voice corpus.</p> <p>See annotations for more details.</p> <h3>Supported Tasks and Leaderboards</h3> <p>Gender classification, Accent classification.</p> <h3>Languages</h3> <p>The dataset is in Catalan (ca).</p> <h2>Dataset Structure</h2> <h3>Instances</h3> <p>Two xlsx documents are published, one for each round of annotations.</p> <p>The following information is available in each of the documents:</p> <p><br><code>{</code><br><code> 'speaker ID': '1b7fc0c4e437188bdf1b03ed21d45b780b525fd0dc3900b9759d0755e34bc25e31d64e69c5bd547ed0eda67d104fc0d658b8ec78277810830167c53ef8ced24b', </code><br><code> 'idx': '31', </code><br><code> 'same speaker': {'AN1': 'SI',</code><br><code> 'AN2': 'SI',</code><br><code> 'AN3': 'SI',</code><br><code> 'agreed': 'SI',</code><br><code> 'percentage': '100'}, </code><br><code> 'gender': {'AN1': 'H',</code><br><code> 'AN2': 'H',</code><br><code> 'AN3': 'H',</code><br><code> 'agreed': 'H',</code><br><code> 'percentage': '100'}, </code><br><code> 'accent': {'AN1': 'Central',</code><br><code> 'AN2': 'Central',</code><br><code> 'AN3': 'Central',</code><br><code> 'agreed': 'Central',</code><br><code> 'percentage': '100'}, </code><br><code> 'audio quality': {'AN1': '4.0',</code><br><code> 'AN2': '3.0',</code><br><code> 'AN3': '3.0',</code><br><code> 'agreed': '3.0',</code><br><code> 'percentage': '66',</code><br><code> 'mean quality': '3.33',</code><br><code> 'stdev quality': '0.58'}, </code><br><code> 'comments': {'AN1': '',</code><br><code> 'AN2': 'pujades i baixades de volum',</code><br><code> 'AN3': 'Deu ser d'alguna zona de transició amb el central, perquè no fa una reducció total vocàlica, però hi té molta tendència'}, </code><br><code>}</code></p> <p> </p> <p>We also publish the document Guia anotació parlants.pdf, with the guidelines the annotators recieved.</p> <h3>Data Fields</h3> <ul> <li>speaker ID (string): An id for which client (voice) made the recording in the Common Voice corpus</li> <li> idx (int): Id in this corpus</li> <li> AN1 (string): Annotations from Annotator 1</li> <li> AN2 (string): Annotations from Annotator 2</li> <li> AN3 (string): Annotations from Annotator 3</li> <li> agreed (string): Annotation from the majority of the annotators</li> <li>percentage (int): Percentage of annotators that agree with the agreed annotation</li> <li>mean quality (float): Mean of the quality annotation</li> <li>stdev quality (float): Standard deviation of the mean quality</li> </ul> <h3>Data Splits</h3> <p>The corpus remains undivided into splits, as its purpose does not involve training models.</p> <h2>Dataset Creation</h2> <h3>Curation Rationale</h3> <p>During 2022, a campaign was launched to promote the Common Voice corpus within the Catalan-speaking community, achieving remarkable success. However, not all participants provided their demographic details such as age, gender, and accent. Additionally, some individuals faced difficulty in self-defining their accent using the standard classifications established by specialists.</p> <p>In order to obtain a balanced corpus with reliable information, we have seen the the necessity of enlisting a group of experts from the University of Barcelona to provide accurate annotations.</p> <p>We release the complete annotations because transparency is fundamental to our project. Furthermore, we believe they hold philological value for studying dialectal and gender variants.</p> <h3>Source Data</h3> <p>The original data comes from the [Catalan sentences of the Common Voice corpus](https://commonvoice.mozilla.org/en/datasets).</p> <p><strong>Initial Data Collection and Normalization</strong></p> <p>We have selected speakers who have recorded more than 1200 seconds of speech in the Catalan set of the <a href="https://commonvoice.mozilla.org/en/datasets">version 13 of the Common Voice corpus</a>.</p> <p><strong>Who are the source language producers?</strong></p> <p>The original data comes from the <a href="https://huggingface.co/datasets/mozilla-foundation/common_voice_16_1/tree/main/transcript/ca">Catalan sentences of the Common Voice corpus</a>.</p> <h3>Annotations</h3> <p><strong>Annotation process</strong></p> <p>Starting with <a href="https://huggingface.co/datasets/mozilla-foundation/common_voice_16_1/tree/main/transcript/ca">version 13 of the Common Voice corpus</a> we identified the speakers (273) who have recorded more than 1200 seconds of speech. </p> <p>A team of three annotators was tasked with annotating:</p> <ul> <li>if all the recordings correspond to the same person</li> <li>the gender of the speaker</li> <li>the accent of the speaker</li> <li>the quality of the recording</li> </ul> <p>They conducted an initial round of annotation, discussed their varying opinions, and subsequently conducted a second round.</p> <p>We release the complete annotations because transparency is fundamental to our project. Furthermore, we believe they hold philological value for studying dialectal and gender variants.</p> <p><strong>Who are the annotators?</strong></p> <p>The annotation was entrusted to the [CLiC (Centre de Llenguatge i Computació)](https://clic.ub.edu/en/que-es-clic) team from the University of Barcelona. <br>They selected a group of three annotators (two men and one woman), who received a scholarship to do this work. </p> <p>The annotation team was composed of:</p> <ul> <li>Annotator 1: 1 female annotator, aged 18-25, L1 Catalan, student in the Modern Languages and Literatures degree, with a focus on Catalan.</li> <li>Annotators 2 & 3: 2 male annotators, aged 18-25, L1 Catalan, students in the Catalan Philology degree.</li> <li>1 female supervisor, aged 40-50, L1 Catalan, graduate in Physics and in Linguistics, Ph.D. in Signal Theory and Communications.</li> </ul> <p>To do the annotation they used a Google Drive spreadsheet</p> <h3>Personal and Sensitive Information</h3> <p>The Common Voice dataset consists of people who have donated their voice online. We don't share here their voices, but their gender and accent. <br>You agree to not attempt to determine the identity of speakers in the Common Voice dataset.</p> <h2>Considerations for Using the Data</h2> <h3>Social Impact of Dataset</h3> <p>The ID come from the Common Voice dataset, that consists of people who have donated their voice online.</p> <p><em>You agree to not attempt to determine the identity of speakers in the Common Voice dataset.</em></p> <p>The information from this corpus will allow us to train and evaluate well balanced Catalan ASR models. Furthermore, we believe they hold philological value for studying dialectal and gender variants.</p> <h3>Discussion of Biases</h3> <p>Most of the voices of the common voice in Catalan correspond to men with a central accent between 40 and 60 years old. The aim of this dataset is to provide information that allows to minimize the biases that this could cause.</p> <p>For the gender annotation, we have only considered "H" (male) and "D" (female).</p> <h3>Other Known Limitations</h3> <p>[N/A]</p> <h2>Additional Information</h2> <h3>Dataset Curators</h3> <p>Language Technologies Unit at the Barcelona Supercomputing Center (langtech@bsc.es)</p> <p>This work has been promoted and financed by the Generalitat de Catalunya through the <a href="https://projecteaina.cat/">Aina project</a>.</p> <h3>Licensing Information</h3> <p>This dataset is licensed under a <a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a> license.</p> <p>It can be used for any purpose, whether academic or commercial, under the terms of the license. <br>Give appropriate credit, provide a link to the license, and indicate if changes were made.</p> <h3>Citation Information</h3> <p><a href="../badge/DOI/10.5281/zenodo.11104388.svg">DOI</a></p> <h3>Contributions</h3> <p>The annotation was entrusted to the <a href="https://stel2.ub.edu/el-servei">STeL</a> team from the University of Barcelona.</p>
Data from "A population of neurons selective for human voice in the monkey brain"
<p>Preprocessed datasets associated to the research article "A population of neurons selective for human voice in the monkey brain", PNAS.</p>
SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge (CtrSVDD Track, Test Set)
<p>For more information about SVDD Challenge 2024, please refer to https://challenge.singfake.org/.<br><br>We have released the test set here.</p> <p>The training and development set is at https://zenodo.org/records/10467648.</p> <p>The Interspeech paper that describes the dataset details and baseline analysis is https://arxiv.org/abs/2406.02438.</p>
Voices from Cabinda: Audio files of the examples in the paper "Você + 2SG in Cabindan Portuguese (Angola): Two Effects of Language Contact" (LaborHistórico)
<p>Audio files of the examples presented throughout the paper "Você + 2SG in Cabindan Portuguese (Angola): Two Effects of Language Contact" (accepted for publication in LaborHistórico). The audio excerpts are taken from my corpus of interviews in Cabinda, which will be made available soon. This fieldwork, conducted in compliance with ethical standards, was made possible through the assistance of the NGO <em>Ajuda de Desenvolvimento de Povo para Povo</em> and with the authorization of the <em>Secretaria Provincial da Cultura </em>in Cabinda. It received funding from the University of Augsburg (<em>Förderung des wissenschaftlichen Nachwuchses</em>).</p>
Voice data in Dioula language relating to the words Yes, No, Call, Next, Previous, Dial, Stop, True, False, Enter and Exit
<p><span>For this project entitled “Development of a speech recognition model for under-resourced languages”, the collected dataset includes audio recordings of native speakers of the Dioula language pronouncing a series of specific keywords such as “Yes”, “No”, “Call”, “Next”, “Previous”, “Dial”, “Stop”, “True”, “False”, “Enter” and “Exit”. These recordings were obtained in diverse environments, with a wide variety of speakers to ensure that the different tones, accents, and phonetic variations specific to Dioula are taken into account. Each audio file was assigned to a category corresponding to the spoken word, creating a class-structured dataset. This corpus will be used to train a speech recognition model using deep learning techniques, with the objective of improving recognition accuracy in real contexts. This database is essential for the design and evaluation of a model capable of facilitating access and voice interaction for the Dioula community.</span></p>
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