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105 results for “pitch”
Climbing parrots achieve pitch stability using axial-appendicular force couples
<p class="Default">During vertical climbing, the gravitational moment tends to pitch the animal's head away from the climbing surface and this may be countered by 1) applying a correcting torque at a discrete contact point, or 2) applying opposing horizontal forces at separate contact points to produce a free moment. We tested these potential strategies in small parrots with an experimental climbing apparatus imitating the fine branches and vines of their natural habitat. The birds climbed on a vertical ladder with four instrumented rungs that measured three-dimensional force and torque, representing the first measurements of multiple contacts from a climbing bird. The parrots ascend primarily by pulling upward from the upper rung using the beak and feet. They resist the gravitational pitching moment with a free moment produced by horizontal force couples between the beak and feet during the first third of the stride and the tail and feet during the last third of the stride. The reaction torque from individual rungs did not counter, but exacerbated the gravitational pitching moment. Possible climbing limitations were explored using two different rung radii, each with low and high friction surfaces. Rung torque was limited in the large-radius, low-friction condition, however, rung condition did not significantly influence free moments produced. These findings have implications for our understanding of avian locomotor modules (i.e., coordinated actions of the head-neck, hindlimbs, and tail), the use of force couples in vertical locomotion, and the evolution of associated structures.</p>
Buy AMX Pitch (December 2016)
<p>Auyon (Alex) Rahman’s pitch to buy AMX to the members, faculty and stakeholders in attendance at the Student Portfolio Investment Fund at the University of Maine, that manages $3.2 million of the University’s endowment.</p> <p> </p> <p>Auyon (Alex) Rahman was able to secure majority votes, and his motion to buy AMX passed.</p>
Selective area epitaxy of GaAs: the unintuitive role of feature size and pitch
<p>Selective area epitaxy (SAE) provides the path for scalable fabrication of semiconductor nanostructures in a device-compatible configuration. In the current paradigm, SAE is understood as localized epitaxy and is modelled by combining planar and self-assembled nanowire growth mechanisms. Here we use GaAs SAE as a model system to provide a different perspective. First, we provide evidence of the significant impact of the annealing stage in the calculation of the growth rates. Then, by elucidating the effect of geometrical constraints on the growth of the semiconductor crystal, we demonstrate the role of adatom desorption and resorption beyond the direct-impingement and diffusion-limited regime. Our theoretical model explains the effect of these constraints on the growth, and in particular why the SAE growth rate is highly sensitive to the pattern geometry. Finally, the disagreement of the model at the largest pitch points to non-negligible multiple adatom recycling between patterned features. Overall, our findings point out the importance of considering adatom diffusion, adsorption and desorption dynamics in designing the SAE pattern to create predetermined nanoscale structures across a wafer. These results are fundamental for the SAE process to become viable in the semiconductor industry.</p>
Meet Me on the Pitch: Developing and Testing a Community-Based Sports and Behavioral Health Intervention for Youth
ClinicalTrials.gov study NCT07339228. IPD Sharing: YES. Countries: 1. Publications: 0.
Osteopathic Manipulative Treatment for Pitch Performance in Baseball Players: A Study on Shoulder and Hip Interventions
ClinicalTrials.gov study NCT07216300. IPD Sharing: YES. Countries: 1. Publications: 0.
Data from: Auditory functional magnetic resonance imaging in dogs – normalization and group analysis and the processing of pitch in the canine auditory pathways
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Data from: Audio-visual interactions uniquely contribute to resolution of visual conflict in people possessing absolute pitch
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Data from: Poor neuro-motor tuning of the human larynx: comparison of sung and whistled pitch imitation
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Data from: Utterance-final position and pitch marking aid word learning in school-age children
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Data from: Linking men‘s voice pitch to actual and perceived trustworthiness across domains
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Climbing parrots achieve pitch stability using axial-appendicular force couples
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Speech and Noise Corpora for Pitch Estimation of Human Speech
<p><em>Part of the dissertation <a href="http://localhost:8000/index.html">Pitch of Voiced Speech in the Short-Time Fourier Transform: Algorithms, Ground Truths, and Evaluation Methods</a>.<br> © 2020, Bastian Bechtold. All rights reserved.</em></p> <p> </p> <p>This dataset contains common speech and noise corpora for evaluating fundamental frequency estimation algorithms as convenient <a href="https://jbof.readthedocs.io/en/latest/">JBOF</a> dataframes. Each corpus is available freely on its own, and allows redistribution:</p> <ul> <li><a href="http://www.festvox.org/cmu_arctic/">CMU-ARCTIC</a> (<em>BSD license) [1]</em></li> <li><a href="http://www.cstr.ed.ac.uk/research/projects/fda/">FDA</a> (<em>free to download)</em> [2]</li> <li><a href="https://lost-contact.mit.edu/afs/nada.kth.se/dept/tmh/corpora/KeelePitchDB/">KEELE</a> (<em>free for noncommercial use</em>) [3]</li> <li><a href="http://www.cstr.ed.ac.uk/research/projects/artic/mocha.html">MOCHA-TIMIT</a> (<em>free for noncommercial use</em>) [4]</li> <li><a href="https://www.spsc.tugraz.at/databases-and-tools/ptdb-tug-pitch-tracking-database-from-graz-university-of-technology.html">PTDB-TUG</a> (<em>ODBL license</em>) [5]</li> <li><a href="http://www.speech.cs.cmu.edu/comp.speech/Section1/Data/noisex.html">NOISEX</a> (<em>free to download</em>) [7]</li> <li><a href="https://research.qut.edu.au/saivt/databases/qut-noise-databases-and-protocols/">QUT-NOISE</a> (<em>CC-BY-SA license</em>) [8]</li> </ul> <p>Additionally, this dataset contains <em>PDAs-0.0.1-py3-none-any.whl</em>, a Python ≥ 3.6 module for Linux, containing several well-known fundamental frequency estimation algorithms:</p> <ul> <li>AUTOC [9]</li> <li>AMDF [10]</li> <li><a href="http://www2.ece.rochester.edu/projects/wcng/code.html">BANA</a> [11]</li> <li>CEP [12]</li> <li><a href="https://github.com/marl/crepe">CREPE</a> [13]</li> <li><a href="http://www.kki.yamanashi.ac.jp/~mmorise/world/english/">DIO</a> [14]</li> <li><a href="http://web.cse.ohio-state.edu/pnl/software.html">DNN</a> [15]</li> <li><a href="https://github.com/LvHang/pitch">KALDI</a> [16]</li> <li>MAPS</li> <li><a href="http://www.seas.ucla.edu/spapl/shareware.html">MBSC</a> [17]</li> <li><a href="https://github.com/jkjaer/fastF0Nls">NLS</a> [18]</li> <li><a href="http://www.ee.ic.ac.uk/hp/staff/dmb/voicebox/voicebox.html">PEFAC</a> [19]</li> <li><a href="https://github.com/praat/praat">PRAAT</a> [20]</li> <li><a href="http://www.speech.kth.se/wavesurfer/links.html">RAPT</a> [21]</li> <li><a href="http://labrosa.ee.columbia.edu/projects/SAcC/">SACC</a> [22]</li> <li><a href="http://www.seas.ucla.edu/spapl/weichu/safe/">SAFE</a> [23]</li> <li><a href="https://mathworks.com/matlabcentral/fileexchange/1230">SHR</a> [24]</li> <li>SIFT [25]</li> <li><a href="https://github.com/covarep/covarep">SRH</a> [26]</li> <li><a href="https://github.com/HidekiKawahara/legacy_straight">STRAIGHT</a> [27]</li> <li><a href="http://www.cise.ufl.edu/~acamacho/english/curriculum.html">SWIPE</a> [28]</li> <li><a href="http://www.ws.binghamton.edu/zahorian/yaapt.htm">YAAPT</a> [29]</li> <li><a href="http://audition.ens.fr/adc/">YIN</a> [30]</li> </ul> <p>The algorithms are included in their native programming language (Matlab for BANA, DNN, MBSC, NLS, NLS2, PEFAC, RAPT, RNN, SACC, SHR, SRH, STRAIGHT, SWIPE, YAAPT, and YIN; C for KALDI, PRAAT, and SAFE; Python for AMDF, AUTOC, CEP, CREPE, MAPS, and SIFT), and adapted to a common Python interface. AMDF, AUTOC, CEP, and SIFT are our partial re-implementations as no original source code could be found.</p> <p>All algorithms have been released as open source software, and are covered by their respective licenses.</p> <p>All of these files are published as part of my dissertation, "<a href="https://bastibe.github.io/Dissertation-Website/">Pitch of Voiced Speech in the Short-Time Fourier Transform: Algorithms, Ground Truths, and Evaluation Methods</a>", and in support of the <a href="https://github.com/bastibe/Replication-Dataset-Scripts">Replication Dataset for Fundamental Frequency Estimation</a>.</p> <p>References:</p> <ol> <li>John Kominek and Alan W Black. CMU ARCTIC database for speech synthesis, 2003.</li> <li>Paul C Bagshaw, Steven Hiller, and Mervyn A Jack. Enhanced Pitch Tracking and the Processing of F0 Contours for Computer Aided Intonation Teaching. In EUROSPEECH, 1993.</li> <li>F Plante, Georg F Meyer, and William A Ainsworth. A Pitch Extraction Reference Database. In Fourth European Conference on Speech Communication and Technology, pages 837–840, Madrid, Spain, 1995.</li> <li>Alan Wrench. MOCHA MultiCHannel Articulatory database: English, November 1999.</li> <li>Gregor Pirker, Michael Wohlmayr, Stefan Petrik, and Franz Pernkopf. A Pitch Tracking Corpus with Evaluation on Multipitch Tracking Scenario. page 4, 2011.</li> <li>John S. Garofolo, Lori F. Lamel, William M. Fisher, Jonathan G. Fiscus, David S. Pallett, Nancy L. Dahlgren, and Victor Zue. TIMIT Acoustic-Phonetic Continuous Speech Corpus, 1993.</li> <li>Andrew Varga and Herman J.M. Steeneken. Assessment for automatic speech recognition: II. NOISEX-92: A database and an experiment to study the effect of additive noise on speech recog- nition systems. Speech Communication, 12(3):247–251, July 1993.</li> <li>David B. Dean, Sridha Sridharan, Robert J. Vogt, and Michael W. Mason. The QUT-NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms. Proceedings of Interspeech 2010, 2010.</li> <li>Man Mohan Sondhi. New methods of pitch extraction. Audio and Electroacoustics, IEEE Transactions on, 16(2):262—266, 1968.</li> <li>Myron J. Ross, Harry L. Shaffer, Asaf Cohen, Richard Freudberg, and Harold J. Manley. Average magnitude difference function pitch extractor. Acoustics, Speech and Signal Processing, IEEE Transactions on, 22(5):353—362, 1974.</li> <li>Na Yang, He Ba, Weiyang Cai, Ilker Demirkol, and Wendi Heinzelman. BaNa: A Noise Resilient Fundamental Frequency Detection Algorithm for Speech and Music. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 22(12):1833–1848, December 2014.</li> <li>Michael Noll. Cepstrum Pitch Determination. The Journal of the Acoustical Society of America, 41(2):293–309, 1967.</li> <li>Jong Wook Kim, Justin Salamon, Peter Li, and Juan Pablo Bello. CREPE: A Convolutional Representation for Pitch Estimation. arXiv:1802.06182 [cs, eess, stat], February 2018. arXiv: 1802.06182.</li> <li>Masanori Morise, Fumiya Yokomori, and Kenji Ozawa. WORLD: A Vocoder-Based High-Quality Speech Synthesis System for Real-Time Applications. IEICE Transactions on Information and Systems, E99.D(7):1877–1884, 2016.</li> <li>Kun Han and DeLiang Wang. Neural Network Based Pitch Tracking in Very Noisy Speech. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 22(12):2158–2168, Decem- ber 2014.</li> <li>Pegah Ghahremani, Bagher BabaAli, Daniel Povey, Korbinian Riedhammer, Jan Trmal, and Sanjeev Khudanpur. A pitch extraction algorithm tuned for automatic speech recognition. In Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, pages 2494–2498. IEEE, 2014.</li> <li>Lee Ngee Tan and Abeer Alwan. Multi-band summary correlogram-based pitch detection for noisy speech. Speech Communication, 55(7-8):841–856, September 2013.</li> <li>Jesper Kjær Nielsen, Tobias Lindstrøm Jensen, Jesper Rindom Jensen, Mads Græsbøll Christensen, and Søren Holdt Jensen. Fast fundamental frequency estimation: Making a statistically efficient estimator computationally efficient. Signal Processing, 135:188–197, June 2017.</li> <li>Sira Gonzalez and Mike Brookes. PEFAC - A Pitch Estimation Algorithm Robust to High Levels of Noise. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 22(2):518—530, February 2014.</li> <li>Paul Boersma. Accurate short-term analysis of the fundamental frequency and the harmonics-to-noise ratio of a sampled sound. In Proceedings of the institute of phonetic sciences, volume 17, page 97—110. Amsterdam, 1993.</li> <li>David Talkin. A robust algorithm for pitch tracking (RAPT). Speech coding and synthesis, 495:518, 1995.</li> <li>Byung Suk Lee and Daniel PW Ellis. Noise robust pitch tracking by subband autocorrelation classification. In Interspeech, pages 707–710, 2012.</li> <li>Wei Chu and Abeer Alwan. SAFE: a statistical algorithm for F0 estimation for both clean and noisy speech. In INTERSPEECH, pages 2590–2593, 2010.</li> <li>Xuejing Sun. Pitch determination and voice quality analysis using subharmonic-to-harmonic ratio. In Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on, volume 1, page I—333. IEEE, 2002.</li> <li>Markel. The SIFT algorithm for fundamental frequency estimation. IEEE Transactions on Audio and Electroacoustics, 20(5):367—377, December 1972.</li> <li>Thomas Drugman and Abeer Alwan. Joint Robust Voicing Detection and Pitch Estimation Based on Residual Harmonics. In Interspeech, page 1973—1976, 2011.</li> <li>Hideki Kawahara, Masanori Morise, Toru Takahashi, Ryuichi Nisimura, Toshio Irino, and Hideki Banno. TANDEM-STRAIGHT: A temporally stable power spectral representation for periodic signals and applications to interference-free spectrum, F0, and aperiodicity estimation. In Acous- tics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on, pages 3933–3936. IEEE, 2008.</li> <li>Arturo Camacho. SWIPE: A sawtooth waveform inspired pitch estimator for speech and music. PhD thesis, University of Florida, 2007.</li> <li>Kavita Kasi and Stephen A. Zahorian. Yet Another Algorithm for Pitch Tracking. In IEEE International Conference on Acoustics Speech and Signal Processing, pages I–361–I–364, Orlando, FL, USA, May 2002. IEEE.</li> <li>Alain de Cheveigné and Hideki Kawahara. YIN, a fundamental frequency estimator for speech and music. The Journal of the Acoustical Society of America, 111(4):1917, 2002.</li> </ol>
Metagenomic analysis of Mesolithic chewed pitch reveals poor oral health among stone age individuals
<p>Prehistoric chewed pitch has proven to be a useful source of ancient DNA, both from humans and their microbiomes. Here we present the metagenomic analysis of three pieces of chewed pitch from Huseby Klev, Sweden, that were dated to 9,890–9,540 before present. The metagenomic profle exposes a Mesolithic oral microbiome that includes opportunistic oral pathogens. We compared the data with healthy and dysbiotic microbiome datasets and we identifed increased abundance of periodontitisassociated microbes. In addition, trained machine learning models predicted dysbiosis with 70–80% probability. Moreover, we identifed DNA sequences from eukaryotic species such as red fox, hazelnut, red deer and apple. Our results indicate a case of poor oral health during the Scandinavian Mesolithic, and show that pitch pieces have the potential to provide information on material use, diet and oral health.</p>
Straw Phonation Exercise Program for Pitch Extension
ClinicalTrials.gov study NCT05357222. IPD Sharing: NO. Countries: 1. Publications: 0.
Radiation Dose From Computed Tomography Before and After Implementation of a High Pitch Dual Spiral Technique
ClinicalTrials.gov study NCT01111760. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Pitch Perception and Memory: Deficits and Training
ClinicalTrials.gov study NCT03707691. IPD Sharing: NO. Countries: 1. Publications: 0.
What is the Influence of a Different Thread Pitch Design on Bone Remodelling Around Conical Southern Oral Implants?
ClinicalTrials.gov study NCT01158664. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Correlation Between Voice Pitch Changes and Tension of Suboccipital Muscles In Normal Subjects
ClinicalTrials.gov study NCT07008859. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Pitch and Loudness Perception by Cochlear Implant Listeners: Psychophysics and Objective Measures
ClinicalTrials.gov study NCT01284790. IPD Sharing: Not stated. Countries: 1. Publications: 0.
PITCH - Impacting Hereditary Cancer Testing
ClinicalTrials.gov study NCT07090109. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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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.
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