The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Bernhard Lehner - One of the best experts on this subject based on the ideXlab platform.
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an introduction to signal processing for singing Voice Analysis high notes in the effort to automate the understanding of vocals in music
IEEE Signal Processing Magazine, 2019Co-Authors: Eric J Humphrey, Sravana Reddy, Prem Seetharaman, Aparna Kumar, Rachel M Bittner, Andrew M Demetriou, Sankalp Gulati, Andreas Jansson, Tristan Jehan, Bernhard LehnerAbstract:Humans have devised a vast array of musical instruments, but the most prevalent instrument remains the human Voice. Thus, techniques for applying audio signal processing methods to the singing Voice are receiving much attention as the world continues to move toward music-streaming services and as researchers seek to unlock the deep content understanding necessary to enable personalized listening experiences on a large scale. This article provides an introduction to the topic of singing-Voice Analysis. It surveys the foundations and state of the art in computational modeling across three main categories of singing: general vocalizations, the musical function of Voice, and the singing of lyrics. We aim to establish a starting point for practitioners new to this field and frame near-field opportunities and challenges on the horizon.
Jussi M. Kärkkäinen - One of the best experts on this subject based on the ideXlab platform.
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Perceptual Assessment and Acoustic Voice Analysis as Screening Tests for Vocal Fold Paresis After Thyroid or Parathyroid Surgery
World Journal of Surgery, 2020Co-Authors: Maria Heikkinen, Elina Penttilä, Mari Qvarnström, Kimmo Mäkinen, Heikki Löppönen, Jussi M. KärkkäinenAbstract:Background The aim of this study was to evaluate the reliability of clinician-based perceptual assessment of Voice and computerized acoustic Voice Analysis as screening tests for vocal fold paresis or paralysis (VFP) after thyroid and parathyroid surgery. Methods This was a prospective study of 181 patients undergoing thyroid or parathyroid procedure with pre and postoperative laryngoscopic vocal fold inspection, perceptual Voice assessment using grade, roughness, breathiness, asthenia, and strain (GRBAS) scale and acoustic Voice Analysis using the multi-dimensional Voice program (MDVP). Patients were divided into 2 groups for comparison; those with new postoperative VFP and those without. Potential screening tools were evaluated using the receiving operating characteristic (ROC) Analysis. Results Fourteen (6.6%) patients had a new postoperative VFP. Postoperative GRBAS scores were significantly ( P 0) had the best sensitivity, 93%, for predicting VFP, but the specificity was only 50%. Postoperative jitter (cut off > 1.60) in MDVP had a good specificity, 90%, but only 50% sensitivity. Combining all the GRBAS and MDVP variables with P
Eric J Humphrey - One of the best experts on this subject based on the ideXlab platform.
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an introduction to signal processing for singing Voice Analysis high notes in the effort to automate the understanding of vocals in music
IEEE Signal Processing Magazine, 2019Co-Authors: Eric J Humphrey, Sravana Reddy, Prem Seetharaman, Aparna Kumar, Rachel M Bittner, Andrew M Demetriou, Sankalp Gulati, Andreas Jansson, Tristan Jehan, Bernhard LehnerAbstract:Humans have devised a vast array of musical instruments, but the most prevalent instrument remains the human Voice. Thus, techniques for applying audio signal processing methods to the singing Voice are receiving much attention as the world continues to move toward music-streaming services and as researchers seek to unlock the deep content understanding necessary to enable personalized listening experiences on a large scale. This article provides an introduction to the topic of singing-Voice Analysis. It surveys the foundations and state of the art in computational modeling across three main categories of singing: general vocalizations, the musical function of Voice, and the singing of lyrics. We aim to establish a starting point for practitioners new to this field and frame near-field opportunities and challenges on the horizon.
Traian Mihaescu - One of the best experts on this subject based on the ideXlab platform.
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Voice Analysis in patients with obstructive sleep apnea syndrome
European Respiratory Journal, 2015Co-Authors: Sinziana Lovin, Corneliu Botez, Traian MihaescuAbstract:Introduction: Human vocal tract is a series of pipes. Repeated breathing pauses during sleep and snoring occurring in Obstructive sleep apnea syndrome (OSAS) induce structural and functional changes in the vocal tract. The effect of treatment by continuous positive airway pressure (CPAP) on acoustic features of Voice in OSAS is still under research. Voice Analysis is expressed in terms of formants, which are the result of energy peaks in a zone of the acoustic spectrum. Methods: In 21 men and in 20 women with severe OSAS we have studied 3 formants considered to be crucial in the generation of vowels: F0 (fundamental frequency), F1 (generated by the pharynx) and F2 (originated in the oral cavity). The Analysis was performed using the Praat Voice Analysis system, while subjects were pronouncing sustained vocals „a” and „e” at initiantion (when diagnosed with OSAS by polysomnography) and after 4 weeks of CPAP therapy. Results: All the formants showed lower values compared to those quoted in the literature as normal for adult European population, in both females and man, most significantly for the F0 of the vowel „a” in women, which was 178,15 ± 29 Hz compared to 192,00 Hz quoted as normative. There was a slight increase in all formants after 4 weeks of CPAP use, although non-significantly ( eg. 185,2 vs 178,15 for F0a in women , p >0.5). Conclusion: Patients with untreated OSAS tend to have lower frequencies of their Voices than general population and the use of CPAP tends to improve this phoniatric aspect.
Andrew M Demetriou - One of the best experts on this subject based on the ideXlab platform.
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an introduction to signal processing for singing Voice Analysis high notes in the effort to automate the understanding of vocals in music
IEEE Signal Processing Magazine, 2019Co-Authors: Eric J Humphrey, Sravana Reddy, Prem Seetharaman, Aparna Kumar, Rachel M Bittner, Andrew M Demetriou, Sankalp Gulati, Andreas Jansson, Tristan Jehan, Bernhard LehnerAbstract:Humans have devised a vast array of musical instruments, but the most prevalent instrument remains the human Voice. Thus, techniques for applying audio signal processing methods to the singing Voice are receiving much attention as the world continues to move toward music-streaming services and as researchers seek to unlock the deep content understanding necessary to enable personalized listening experiences on a large scale. This article provides an introduction to the topic of singing-Voice Analysis. It surveys the foundations and state of the art in computational modeling across three main categories of singing: general vocalizations, the musical function of Voice, and the singing of lyrics. We aim to establish a starting point for practitioners new to this field and frame near-field opportunities and challenges on the horizon.
