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263 results for “listening”
Figure 3 from: Ting JJ, Judge KA, Gwynne DT (2017) Listening to male song induces female field crickets to differentially allocate reproductive resources. Journal of Orthoptera Research 26: 205-210. https://doi.org/10.3897/jor.26.19891
Figure 3 - Mean (±SE) size of embryos laid during: the first week following treatment (Week 1), and the subsequent weeks following treatment (Post Week 1) of females who experienced either low- (grey symbols) or high- (black symbols) quality calling song.
Figure 2 from: Ting JJ, Judge KA, Gwynne DT (2017) Listening to male song induces female field crickets to differentially allocate reproductive resources. Journal of Orthoptera Research 26: 205-210. https://doi.org/10.3897/jor.26.19891
Figure 2 - Mean (±SE) change in mass during: the first week following treatment (Week 1), and the subsequent weeks following treatment (Post Week 1) of females who experienced either low- (grey symbols) or high- (black symbols) quality calling song.
Figure 1 from: Ting JJ, Judge KA, Gwynne DT (2017) Listening to male song induces female field crickets to differentially allocate reproductive resources. Journal of Orthoptera Research 26: 205-210. https://doi.org/10.3897/jor.26.19891
Figure 1 - Mean (±SE) latency of females to choose the speaker broadcasting either low- or high-quality calling song.
Figure 4 from: Ting JJ, Judge KA, Gwynne DT (2017) Listening to male song induces female field crickets to differentially allocate reproductive resources. Journal of Orthoptera Research 26: 205-210. https://doi.org/10.3897/jor.26.19891
Figure 4 - Mean (±SE) embryo laying rate during: the first week following treatment (Week 1), and the subsequent weeks following treatment (Post Week 1) of females who experienced either low- (grey symbols) or high- (black symbols) quality calling song.
STRATEGIES FOR BOOSTING LERANERS' LISTENING COMPETENCE
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Data to accompany "Evaluation of Spatial Audio Reproduction Methods (Part 2): Analysis of Listener Preference", J. AES, 2016
<p>This work was supported by the EPSRC Programme Grant S3A: Future Spatial Audio for an Immersive Listener Experience at Home (EP/L000539/1). Details about the data underlying this work, along with the terms for data access, are available from http://dx.doi.org/10.15126/surreydata.00809533</p> <p>If you use the data, please cite the following paper:</p> <p>J. Francombe, T. Brookes, and R. Mason, 2016: Evaluation of Spatial Audio Reproduction Methods (Part 2): Analysis of Listener Preference. Journal of the Audio Engineering Society</p>
A BRIEF OVERVIEW OF LANGUAGE SKILLS: SPEAKING, LISTENING, READING, AND WRITING
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Passive Head-Mounted Display Music-Listening EEG dataset
<p><strong>Summary:</strong></p> <p>This dataset contains electroencephalographic recordings of 12 subjects listening to music with and without a passive head-mounted display, that is, a head-mounted display which does not include any electronics at the exception of a smartphone. The electroencephalographic headset consisted of 16 electrodes. A full description of the experiment is available at <a href="https://hal.archives-ouvertes.fr/hal-02085118">https://hal.archives-ouvertes.fr/hal-02085118</a>. Data were recorded during a pilot experiment taking place in the GIPSA-lab, Grenoble, France, in 2017 (Cattan and al, 2018). Python code for manipulating the data is downloadable at <a href="https://github.com/plcrodrigues/py.PHMDML.EEG.2017-GIPSA">https://github.com/plcrodrigues/py.PHMDML.EEG.2017-GIPSA</a>. The ID of this dataset is <em>PHMDML.EEG.2017-GIPSA.</em></p> <p> </p> <p><strong>Full description of the experiment and dataset: </strong><a href="https://hal.archives-ouvertes.fr/hal-02085118">https://hal.archives-ouvertes.fr/hal-02085118</a></p> <p> </p> <p><strong><em>Principal Investigator</em>:</strong> Eng. Grégoire Cattan</p> <p> </p> <p><strong><em>Technical Supervisors</em>:</strong> Eng. Pedro L. C. Rodrigues</p> <p> </p> <p><strong><em>Scientific Supervisor:</em></strong> Dr. Marco Congedo</p> <p> </p> <p><strong>ID of the dataset: </strong><em>PHMDML.EEG.2017-GIPSA</em></p>
ASVspoof 2019 LA Listening Test Data for Partial Rank Similarity MOS Prediction
<p>This dataset is a derivitave work of the ASVSpoof 2019 LA condition listening test data found here:<br> https://datashare.ed.ac.uk/handle/10283/3336<br> -> LA.zip</p> <p>"ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech" <br> Xin Wang, Junichi Yamagishi, Massimiliano Todisco, Héctor Delgado, Andreas Nautsch, Nicholas Evans, Md Sahidullah, Ville Vestman, Tomi Kinnunen, Kong Aik Lee, Lauri Juvela, Paavo Alku, Yu-Huai Peng, Hsin-Te Hwang, Yu Tsao, Hsin-Min Wang, Sébastien Le Maguer, Markus Becker, Fergus Henderson, Rob Clark, Yu Zhang, Quan Wang, Ye Jia, Kai Onuma, Koji Mushika, Takashi Kaneda, Yuan Jiang, Li-Juan Liu, Yi-Chiao Wu, Wen-Chin Huang, Tomoki Toda, Kou Tanaka, Hirokazu Kameoka, Ingmar Steiner, Driss Matrouf, Jean-François Bonastre, Avashna Govender, Srikanth Ronanki, Jing-Xuan Zhang, Zhen-Hua Ling.<br> Computer Speech and Language Colume 64, 2020.</p> <p>This form of the data was used for the PRS paper accepted to ASRU 2023:</p> <p>"Partial Rank Similarity Minimization Method for Quality MOS Prediction of <br> Unseen Speech Synthesis Systems in Zero-shot and Semi-supervised Setting."<br> Hemant Yadav, Erica Cooper, Junichi Yamagishi, Sunayana Sitaram, Rajiv Ratn Shah.</p> <p>Modifications to the original data include converting audio from flac -> wav, sv56 normalization, conversion of labels from an 0-9 rating scale to a 1-5 scale, and creation of training/development/testing splits.</p>
Bayesian Surprise Predicts Human Event Segmentation in Story Listening
<p>This repository contains data and code for the paper: <a href="https://psyarxiv.com/qd2ra/">https://psyarxiv.com/qd2ra/</a></p><p>The embeddings and outputs from GPT-2 are in the extract-embeddings-data.zip file.</p><p>The button press data is in the button-press-proportions.zip file. Button press measures computed using kernel density estimates are stored in files with the suffix "density".</p><p>The derived measures of disfluency are in the disfluency_measures.zip file. In this folder the files {story_name}_processed.csv contain the disfluency measures for each story.</p><p>The results from the analysis are in the results.zip and supplementary_results_kernel_density.zip files.</p><p>The code is available at <a href="https://github.com/manojneuro/bayesiansurprise">https://github.com/manojneuro/bayesiansurprise</a></p>
Listening test data for "Investigating Range-Equalizing Bias in Mean Opinion Score Ratings of Synthesized Speech"
<p>This is the listening test data for the paper published at Interspeech 2023:<br>"Investigating Range-Equalizing Bias in Mean Opinion Score Ratings of Synthesized Speech"<br>Erica Cooper and Junichi Yamagishi<br>doi: 10.21437/Interspeech.2023-1076</p><p>Please cite this paper if you use this data in your work.</p><p>The audio data used in this study comes from past editions of the Blizzard Challenge, Voice Conversion Challenge, and published samples from ESPnet-TTS. Audio samples are not included in this dataset but instructions for obtaining them are included.</p>
Benefits of Assistive Listening Device for Speech Intelligibility
ClinicalTrials.gov study NCT05072470. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Analgesic Effect of Music Listening During Pain Elicitation in Fibromyalgia
ClinicalTrials.gov study NCT04059042. IPD Sharing: NO. Countries: 1. Publications: 0.
Clinical Application of Listening to Music to Prevent Delirium in the Intensive Care Unit
ClinicalTrials.gov study NCT07369258. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
The Effect of Lullaby Listened to Preterm Babies in Neonatal Intensive Care Units on Physiological Parameters and Pain
ClinicalTrials.gov study NCT05253625. IPD Sharing: NO. Countries: 0. Publications: 12.
Multi-center Study to Examine Changes to the Environment Surrounding the Electrodes in the Cochlea and to Capture the Most Challenging Listening Environments Experienced by Persons With a Cochlear Imp
ClinicalTrials.gov study NCT06173687. IPD Sharing: NO. Countries: 3. Publications: 0.
The Effect of Different Music Listened During Retinopathy Examination to Premature Infants
ClinicalTrials.gov study NCT05967572. IPD Sharing: NO. Countries: 1. Publications: 0.
Can Listening to Music Improve Attention and Language After Post-Stroke Aphasia?
ClinicalTrials.gov study NCT07198048. IPD Sharing: YES. Countries: 0. Publications: 2.
Magnetic Resonance Imaging of the Effect of Music Listening on Brain Activity Under Anesthesia
ClinicalTrials.gov study NCT04464265. IPD Sharing: NO. Countries: 1. Publications: 0.
fNIRS, Listening Effort, and Motivation
ClinicalTrials.gov study NCT05893992. IPD Sharing: NO. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.