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1

Masih, Dawa A. A., Nawzad K. Jalal, Manar N. A. Mohammed, and Sulaiman A. Mustafa. "The Assessment of Acoustical Characteristics for Recent Mosque Buildings in Erbil City of Iraq." ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY 9, no. 1 (March 1, 2021): 51–66. http://dx.doi.org/10.14500/aro.10784.

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The study of mosque acoustics, concerning acoustical features, sound quality for speech intelligibility, and additional practical acoustic criteria, is commonly overlooked. Acoustic quality is vital to the fundamental use of mosques, in terms of contributing toward prayers and worshippers’ appreciation. This paper undertakes a comparative analysis of the acoustic quality level and the acoustical characteristics for two modern mosque buildings constructed in Erbil city. This work investigates and examines the acoustical quality and performance of these two mosques and their prayer halls through room simulation using ODEON Room Acoustics Software, to assess the degree of speech intelligibility according to acoustic criteria relative to the spatial requirements and design guidelines. The sound pressure level and other room-acoustic indicators, such as reverberation time (T30), early decay time, and speech transmission index, are tested. The outcomes demonstrate the quality of acoustics in the investigated mosques during semi-occupied and fully-occupied circumstances. The results specify that the sound quality within the both mosques is displeasing as the loudspeakers were off.
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2

Duran, Sebastian, Martyn Chambers, and Ioannis Kanellopoulos. "An Archaeoacoustics Analysis of Cistercian Architecture: The Case of the Beaulieu Abbey." Acoustics 3, no. 2 (March 26, 2021): 252–69. http://dx.doi.org/10.3390/acoustics3020018.

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The Cistercian order is of acoustic interest because previous research has hypothesized that Cistercian architectural structures were designed for longer reverberation times in order to reinforce Gregorian chants. The presented study focused on an archaeoacacoustics analysis of the Cistercian Beaulieu Abbey (Hampshire, England, UK), using Geometrical Acoustics (GA) to recreate and investigate the acoustical properties of the original structure. To construct an acoustic model of the Abbey, the building’s dimensions and layout were retrieved from published archaeology research and comparison with equivalent structures. Absorption and scattering coefficients were assigned to emulate the original room surface materials’ acoustics properties. CATT-Acoustics was then used to perform the acoustics analysis of the simplified building structure. Shorter reverberation time (RTs) was generally observed at higher frequencies for all the simulated scenarios. Low speech intelligibility index (STI) and speech clarity (C50) values were observed across Abbey’s nave section. Despite limitations given by the impossibility to calibrate the model according to in situ measurements conducted in the original structure, the simulated acoustics performance suggested how the Abbey could have been designed to promote sacral music and chants, rather than preserve high speech intelligibility.
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3

Askenfelt, Anders G., and Britta Hammarberg. "Speech Waveform Perturbation Analysis." Journal of Speech, Language, and Hearing Research 29, no. 1 (March 1986): 50–64. http://dx.doi.org/10.1044/jshr.2901.50.

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The performance of seven acoustic measures of cycle-to-cycle variations (perturbations) in the speech waveform was compared. All measures were calculated automatically and applied on running speech. Three of the measures refer to the frequency of occurrence and severity of waveform perturbations in special selected parts of the speech, identified by means of the rate of change in the fundamental frequency. Three other measures refer to statistical properties of the distribution of the relative frequency differences between adjacent pitch periods. One perturbation measure refers to the percentage of consecutive pitch period differences with alternating signs. The acoustic measures were tested on tape recorded speech samples from 41 voice patients, before and after successful therapy. Scattergrams of acoustic waveform perturbation data versus an average of perceived deviant voice qualities, as rated by voice clinicians, are presented. The perturbation measures were compared with regard to the acoustic-perceptual correlation and their ability to discriminate between normal and pathological voice status. The standard deviation of the distribution of the relative frequency differences was suggested as the most useful acoustic measure of waveform perturbations for clinical applications.
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4

Chenausky, Karen, Joel MacAuslan, and Richard Goldhor. "Acoustic Analysis of PD Speech." Parkinson's Disease 2011 (2011): 1–13. http://dx.doi.org/10.4061/2011/435232.

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According to the U.S. National Institutes of Health, approximately 500,000 Americans have Parkinson's disease (PD), with roughly another 50,000 receiving new diagnoses each year. 70%–90% of these people also have the hypokinetic dysarthria associated with PD. Deep brain stimulation (DBS) substantially relieves motor symptoms in advanced-stage patients for whom medication produces disabling dyskinesias. This study investigated speech changes as a result of DBS settings chosen to maximize motor performance. The speech of 10 PD patients and 12 normal controls was analyzed for syllable rate and variability, syllable length patterning, vowel fraction, voice-onset time variability, and spirantization. These were normalized by the controls' standard deviation to represent distance from normal and combined into a composite measure. Results show that DBS settings relieving motor symptoms can improve speech, making it up to three standard deviations closer to normal. However, the clinically motivated settings evaluated here show greater capacity to impair, rather than improve, speech. A feedback device developed from these findings could be useful to clinicians adjusting DBS parameters, as a means for ensuring they do not unwittingly choose DBS settings which impair patients' communication.
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5

M, Manjutha. "Acoustic Analysis of Formant Frequency Variation in Tamil Stuttered Speech." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 2934–44. http://dx.doi.org/10.5373/jardcs/v12sp7/20202438.

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6

Weedon, B., E. Hellier, J. Edworthy, and K. Walters. "Perceived Urgency in Speech Warnings." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 22 (July 2000): 690–93. http://dx.doi.org/10.1177/154193120004402251.

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Two experiments are reported that investigate the effects of acoustics and semantics in verbal warnings. In the first experiment subjects rated the urgency of warning signal words spoken in different presentation styles (URGENT, NON-URGENT, MONOTONE). Significant differences in urgency ratings were found between presentation styles. Acoustic analysis revealed how acoustic parameters differed within these different presentation styles. These acoustic measurements were used to construct synthesised speech warnings that differed in urgency. They were rated in experiment 2 and the predicted differences between the urgency of the words were found. These studies indicate that urgency in natural speech is produced by alterations in a few acoustic parameters and that these alterations can easily be incorporated into synthetic speech to reproduce variations in urgency.
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7

Keller, Eric, Patrick Vigneux, and Martine Laframboise. "Acoustic analysis of neurologically impaired speech." International Journal of Language & Communication Disorders 26, no. 1 (January 1991): 75–94. http://dx.doi.org/10.3109/13682829109011993.

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8

Thakore, Jogin, Viliam Rapcan, Shona Darcy, Sherlyn Yeap, Natasha Afzal, and Richard Reilly. "Acoustic and temporal analysis of speech." International Clinical Psychopharmacology 26 (September 2011): e131. http://dx.doi.org/10.1097/01.yic.0000405855.63819.e2.

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9

Sondhi, Savita, Munna Khan, Ritu Vijay, Ashok K. Salhan, and Satish Chouhan. "Acoustic analysis of speech under stress." International Journal of Bioinformatics Research and Applications 11, no. 5 (2015): 417. http://dx.doi.org/10.1504/ijbra.2015.071942.

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10

O'Shaughnessy, Douglas. "Acoustic Analysis for Automatic Speech Recognition." Proceedings of the IEEE 101, no. 5 (May 2013): 1038–53. http://dx.doi.org/10.1109/jproc.2013.2251592.

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11

Bunta, Ferenc. "Speech Science Applications for Practicing Clinicians and Audiology or Speech-Language Pathology Students." Perspectives on Speech Science and Orofacial Disorders 25, no. 2 (October 2015): 81–93. http://dx.doi.org/10.1044/ssod25.2.81.

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The advent of widely available, free, and user-friendly speech analysis software in the late 1990s has made it possible to perform acoustic analyses in clinical and educational settings. However, despite the widespread availability and relative ease of use of speech analysis programs, some clinicians are reluctant to adopt hands-on acoustic analyses into their practice. The purpose of the present paper is threefold: (1) to dispel the myth that speech science and acoustic analyses are difficult and only marginally useful for clinical practice, (2) to demonstrate the practical utility—even necessity—of acoustic analyses for practicing as well as future audiologists and speech-language pathologists, and (3) to briefly outline a highly interactive speech science course with integrated hands-on acoustic analyses. Today, more than ever before, a solid background in speech science and extensive experience with acoustic analyses is a necessary part of audiologists' and speech-language pathologists' education, because incorporating speech analyses can enhance clinical practice. Moreover, new technologies demand that clinicians understand the principles behind the programs they and their clients use.
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12

Abdullah, Abdul Hakim, and Zamir A. Zulkefli. "A Study of the Acoustics and Speech Intelligibility Quality of Mosques in Malaysia." Applied Mechanics and Materials 564 (June 2014): 129–34. http://dx.doi.org/10.4028/www.scientific.net/amm.564.129.

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This study presents the assessment of the quality of speech intelligibility of two Malaysian mosques and the results are used to develop a set of general acoustical guidelines to be used in the design of a mosque. Two mosques were selected for the research: Masjid UPM and the Masjid Jamek. The objective of the research is to enable the comparison of the acoustics and speech intelligibility between the mosques as function of the size, volume, occupancy and other parameters of the main prayer hall on the acoustic and speech intelligibility of the respective mosques. The reverberation time (RT60), speech level (SL), background noise (BN), signal-to-noise ratio (S/N ratio) were determined and are used to develop the speech transmission index (STI) and rapid transmission index (RASTI) prediction models for both mosques. It was observed from the results that the RT60, STI and RASTI values shows better performance over number of occupancy for both mosques. Furthermore, the BN and SL results were visualized using the spatial distribution patterns (SDP) of the main hall. The results of the analysis show that the overall acoustic and speech quality of Masjid Jamek is better when compared to the overall acoustic and speech quality of Masjid UPM. These results are then used to develop a set of design recommendations to ensure adequate speech intelligibility quality a mosque.
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13

손남호, Hwang Hyosung, and Ho-Young Lee. "Emotional Speech Database and the Acoustic Analysis of Emotional Speech." EONEOHAG ll, no. 72 (August 2015): 175–99. http://dx.doi.org/10.17290/jlsk.2015..72.175.

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14

Sivaraman, Ganesh, Carol Espy-Wilson, Vikramjit Mitra, Hosung Nam, and Elliot Saltzman. "Analysis of acoustic to articulatory speech inversion for natural speech." Journal of the Acoustical Society of America 136, no. 4 (October 2014): 2082. http://dx.doi.org/10.1121/1.4899477.

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15

Радовановић, Драгана, and Снежана Гудурић. "АКУСТИЧКЕ ОСОБЕНОСТИ ФРИКАТИВА /Ш/ И /Ж/ У БАТАЊИ (МАЂАРСКА) И НАЋФАЛИ (РУМУНИЈА)." ИСХОДИШТА 1, no. 7 (July 8, 2021): 369–83. http://dx.doi.org/10.46630/ish.7.2021.25.

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This paper deals with the acoustic nature of fricative palatal consonants [ʃ], [ʒ] in the speech of Batanja and Nacfala. The obtained results were compared with the acoustic nature of the equivalent consonants in standard Serbian and in the speech of Novi Sad. The results show that the fricatives [ʃ] and [ʒ] of Batanja and Nacfala speeches differ from standard Serbian and Novi Sad speech, but also they differ between themselves. This research also represents an introduction of the acoustic analysis of the speech of Batanja and Nacfala.
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16

Scott, Sophie, and Peter Howell. "Perceptual centers in speech: An acoustic analysis." Journal of the Acoustical Society of America 92, no. 4 (October 1992): 2443. http://dx.doi.org/10.1121/1.404580.

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17

Jovičić, Slobodan T., and Zoran Šarić. "Acoustic Analysis of Consonants in Whispered Speech." Journal of Voice 22, no. 3 (May 2008): 263–74. http://dx.doi.org/10.1016/j.jvoice.2006.08.012.

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18

Liu, Sisi, Yasheng Jin, and Hongzhi Yu. "An Acoustic Analysis for Infants Speech Syllables." SHS Web of Conferences 17 (2015): 02003. http://dx.doi.org/10.1051/shsconf/20151702003.

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19

Gordon, John W. "Acoustic‐phonetic analysis of stress‐induced speech." Journal of the Acoustical Society of America 85, S1 (May 1989): S57—S58. http://dx.doi.org/10.1121/1.2027046.

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20

Caruso, Anthony J., A. Wilcox, J. Anthony Seikel, and Patti Haight. "Acoustic analysis of amyotrophic lateral sclerosis speech." Journal of the Acoustical Society of America 79, S1 (May 1986): S38—S39. http://dx.doi.org/10.1121/1.2023206.

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21

Panek, Daria, Andrzej Skalski, Janusz Gajda, and Ryszard Tadeusiewicz. "Acoustic analysis assessment in speech pathology detection." International Journal of Applied Mathematics and Computer Science 25, no. 3 (September 1, 2015): 631–43. http://dx.doi.org/10.1515/amcs-2015-0046.

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Abstract Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients. In this work, a vector made up of 28 acoustic parameters is evaluated using principal component analysis (PCA), kernel principal component analysis (kPCA) and an auto-associative neural network (NLPCA) in four kinds of pathology detection (hyperfunctional dysphonia, functional dysphonia, laryngitis, vocal cord paralysis) using the a, i and u vowels, spoken at a high, low and normal pitch. The results indicate that the kPCA and NLPCA methods can be considered a step towards pathology detection of the vocal folds. The results show that such an approach provides acceptable results for this purpose, with the best efficiency levels of around 100%. The study brings the most commonly used approaches to speech signal processing together and leads to a comparison of the machine learning methods determining the health status of the patient
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22

Read, Charles, Eugene H. Buder, and Raymond D. Kent. "Speech Analysis Systems." Journal of Speech, Language, and Hearing Research 35, no. 2 (April 1992): 314–32. http://dx.doi.org/10.1044/jshr.3502.314.

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Performance characteristics are reviewed for seven systems marketed for acoustic speech analysis: CSpeech, CSRE, ILS-PC, Kay Elemetrics model 5500 Sona-Graph, MacSpeech Lab II, MSL, and Signalyze. The characteristics reviewed include system components, basic capabilities (signal acquisition, waveform operations, analysis, and other functions), documentation, user interface, data formats and journaling, speed and precision of spectral analysis, and speed and precision of fundamental frequency analysis. Basic capabilities are also tabulated for three recently introduced systems: the Sensimetrics SpeechStation, the Kay Elemetrics Computerized Speech Lab (CSL), and the LSI Speech Workstation. In addition to the capability and performance summaries, this article offers suggestions for continued development of speech analysis systems, particularly in data exchange, journaling, display features, spectral analysis, and fundamental frequency analysis.
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23

Yamamoto, Katsuhiko, Toshio Irino, Toshie Matsui, Shoko Araki, Keisuke Kinoshita, and Tomohiro Nakatani. "Analysis of acoustic features for speech intelligibility prediction models analysis of acoustic features for speech intelligibility prediction models." Journal of the Acoustical Society of America 140, no. 4 (October 2016): 3114. http://dx.doi.org/10.1121/1.4969744.

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24

Odya, Piotr, Jozef Kotus, Adam Kurowski, and Bozena Kostek. "Acoustic Sensing Analytics Applied to Speech in Reverberation Conditions." Sensors 21, no. 18 (September 21, 2021): 6320. http://dx.doi.org/10.3390/s21186320.

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The paper aims to discuss a case study of sensing analytics and technology in acoustics when applied to reverberation conditions. Reverberation is one of the issues that makes speech in indoor spaces challenging to understand. This problem is particularly critical in large spaces with few absorbing or diffusing surfaces. One of the natural remedies to improve speech intelligibility in such conditions may be achieved through speaking slowly. It is possible to use algorithms that reduce the rate of speech (RoS) in real time. Therefore, the study aims to find recommended values of RoS in the context of STI (speech transmission index) in different acoustic environments. In the experiments, speech intelligibility for six impulse responses recorded in spaces with different STIs is investigated using a sentence test (for the Polish language). Fifteen subjects with normal hearing participated in these tests. The results of the analytical analysis enabled us to propose a curve specifying the maximum RoS values translating into understandable speech under given acoustic conditions. This curve can be used in speech processing control technology as well as compressive reverse acoustic sensing.
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25

Silva, Wellington da, and Ana Carolina Constantini. "Speech task affects the objective evaluation of dysphonic voices." Journal of Speech Sciences 7, no. 1 (June 30, 2018): 1–15. http://dx.doi.org/10.20396/joss.v7i1.14988.

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The acoustic analysis of speech has proved useful in the clinical evaluation of dysphonia, for it allows an objective assessment of the voice. However, the literature has suggested that the type of speech task used to obtain voice samples from patients (sustained vowel or connected speech) may affect both the perceptual and the acoustic evaluation of dysphonic voices. This study aimed at investigating whether the type of speech task significantly influences the acoustic analysis of dysphonic voices. Five acoustic parameters related to voice quality (cepstral peak prominence, difference between the magnitudes of the first and second harmonics, harmonics-to-noise ratio, jitter and shimmer) were automatically computed from voice samples of 5 female and 5 male subjects with and without dysphonia. These recordings consisted of three types of speech task: connected speech, count and sustained vowel. Analyses of variance with repeated measures showed that all five acoustic parameters were significantly affected by speech task. Further analyses through the Duncan’s multiple-range test indicated that the type of speech task may also influence the discrimination of dysphonic voices. It is concluded that speech task affects the acoustic assessment of dysphonic voices by significantly raising or reducing the values of the acoustic parameters.
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26

Parjane, Natalia, Sunghye Cho, Sharon Ash, Katheryn A. Q. Cousins, Sanjana Shellikeri, Mark Liberman, Leslie M. Shaw, David J. Irwin, Murray Grossman, and Naomi Nevler. "Digital Speech Analysis in Progressive Supranuclear Palsy and Corticobasal Syndromes." Journal of Alzheimer's Disease 82, no. 1 (June 29, 2021): 33–45. http://dx.doi.org/10.3233/jad-201132.

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Background: Progressive supranuclear palsy syndrome (PSPS) and corticobasal syndrome (CBS) as well as non-fluent/agrammatic primary progressive aphasia (naPPA) are often associated with misfolded 4-repeat tau pathology, but the diversity of the associated speech features is poorly understood. Objective: Investigate the full range of acoustic and lexical properties of speech to test the hypothesis that PSPS-CBS show a subset of speech impairments found in naPPA. Methods: Acoustic and lexical measures, extracted from natural, digitized semi-structured speech samples using novel, automated methods, were compared in PSPS-CBS (n = 87), naPPA (n = 25), and healthy controls (HC, n = 41). We related these measures to grammatical performance and speech fluency, core features of naPPA, to neuropsychological measures of naming, executive, memory and visuoconstructional functioning, and to cerebrospinal fluid (CSF) phosphorylated tau (pTau) levels in patients with available biofluid analytes. Results: Both naPPA and PSPS-CBS speech produced shorter speech segments, longer pauses, higher pause rates, reduced fundamental frequency (f0) pitch ranges, and slower speech rate compared to HC. naPPA speech was distinct from PSPS-CBS with shorter speech segments, more frequent pauses, slower speech rate, reduced verb production, and higher partial word production. In both groups, acoustic duration measures generally correlated with speech fluency, measured as words per minute, and grammatical performance. Speech measures did not correlate with standard neuropsychological measures. CSF pTau levels correlated with f0 range in PSPS-CBS and naPPA. Conclusion: Lexical and acoustic speech features of PSPS-CBS overlaps those of naPPA and are related to CSF pTau levels.
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27

Debruyne, F., P. Delaere, J. Wouters, and P. Uwents. "Acoustic analysis of tracheo-oesophageal versus oesophageal speech." Journal of Laryngology & Otology 108, no. 4 (April 1994): 325–28. http://dx.doi.org/10.1017/s0022215100126660.

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AbstractIn order to evaluate the vocal quality of tracheo-oesophageal and oesophageal speech, several objective acoustic parameters were measured in the acoustic waveform (fundamental frequency, waveform perturbation) and in the frequency spectrum (harmonic prominence, spectral slope). Twelve patients using tracheo-oesophageal speech (with the Provox® valve) and 12 patients using oesophageal speech for at least two months, participated.The main results were that tracheo-oesophageal voices more often showed a detectable fundamental frequency, and that this fundamental frequency was fairly stable; there was also a tendency to more clearly defined harmonics in tracheo-oesophageal speech. This suggests a more regular vibratory pattern in the pharyngo-oesophageal segment, due to the more efficient respiratory drive in tracheo-oesophageal speech. So, a better quality of the voice can be expected, in addition to the longer phonation time and higher maximal intensity.
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28

Mandulak, Kerry Callahan. "“I Can See What You’re Saying”: Clinical Utility of Spectral Moment Analysis." Perspectives on Speech Science and Orofacial Disorders 21, no. 2 (October 2011): 44–54. http://dx.doi.org/10.1044/ssod21.2.44.

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Spectral moment analysis (SMA) is an acoustic analysis tool that shows promise for enhancing our understanding of normal and disordered speech production. It can augment auditory-perceptual analysis used to investigate differences across speakers and groups and can provide unique information regarding specific aspects of the speech signal. The purpose of this paper is to illustrate the utility of SMA as a clinical measure for both clinical speech production assessment and research applications documenting speech outcome measurements. Although acoustic analysis has become more readily available and accessible, clinicians need training with, and exposure to, acoustic analysis methods in order to integrate them into traditional methods used to assess speech production.
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Schuster, Maria, Andreas Maier, Tino Haderlein, Ulrich Eysholdt, and Elmar Noeth. "Automatic acoustic analysis of substitute speech characteristica by speech recognition technique." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3890. http://dx.doi.org/10.1121/1.2935838.

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30

Overath, Tobias, and Joon H. Paik. "From acoustic to linguistic analysis of temporal speech structure: Acousto-linguistic transformation during speech perception using speech quilts." NeuroImage 235 (July 2021): 117887. http://dx.doi.org/10.1016/j.neuroimage.2021.117887.

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31

Drummond, Sakina, Kathy Krueger, Jess Dancer, and Gretchen Spring. "Perceptual and Acoustical Analysis of Alaryngeal Speech: Determinants of Intelligibility." Perceptual and Motor Skills 83, no. 3 (December 1996): 801–2. http://dx.doi.org/10.2466/pms.1996.83.3.801.

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The speech productions of 8 male alaryngeal speakers were used to identify four perceptual measures and five durational measures which were significant for identifying intelligibility of alaryngeal speech. The acoustic variable of duration was a key factor in relating perceptual and acoustic measures.
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32

Hickson, Louise, and Nick Thyer. "Acoustic Analysis of Speech through a Hearing Aid: Perceptual Effects of Changes with Two-Channel Compression." Journal of the American Academy of Audiology 14, no. 08 (September 2003): 414–26. http://dx.doi.org/10.1055/s-0040-1715932.

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Compression amplification significantly alters the acoustic speech signal in comparison to linear amplification. The central hypothesis of the present study was that the compression settings of a two-channel aid that best preserved the acoustic properties of speech compared to linear amplification would yield the best perceptual results, and that the compression settings that most altered the acoustic properties of speech compared to linear would yield significantly poorer speech perception. On the basis of initial acoustic analysis of the test stimuli recorded through a hearing aid, two different compression amplification settings were chosen for the perceptual study. Participants were 74 adults with mild to moderate sensorineural hearing impairment. Overall, the speech perception results supported the hypothesis. A further aim of the study was to determine if variation in participants' speech perception with compression amplification (compared to linear amplification) could be explained by the individual characteristics of age, degree of loss, dynamic range, temporal resolution, and frequency selectivity; however, no significant relationships were found.
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33

Truslow, Eric O., and Helen M. Hanson. "KlattWare tools for acoustic analysis of speech signals." Journal of the Acoustical Society of America 128, no. 4 (October 2010): 2290. http://dx.doi.org/10.1121/1.3508041.

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34

Muta, Hiroshi, Thomas Baer, and Hiroyuki Fukuda. "Acoustic analysis of hoarse voices in running speech." Journal of the Acoustical Society of America 82, S1 (November 1987): S18. http://dx.doi.org/10.1121/1.2024689.

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35

Laccourreye, Ollivier, Lise Crevier-Buchman, Véronique Jouffre, Henri Laccourreye, Daniel Brasnu, and Gregory Weinstein. "Acoustic parameters and speech analysis after supracricoid hemilaryngopharyngectomy." Laryngoscope 105, no. 11 (November 1995): 1223–26. http://dx.doi.org/10.1288/00005537-199511000-00016.

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36

Harris, Katherine S. "Speech research from acoustic transmission to gestural analysis." Journal of the Acoustical Society of America 103, no. 5 (May 1998): 3024. http://dx.doi.org/10.1121/1.422541.

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37

Sarma, Biswajit Dev, and S. R. Mahadeva Prasanna. "Acoustic–Phonetic Analysis for Speech Recognition: A Review." IETE Technical Review 35, no. 3 (April 26, 2017): 305–27. http://dx.doi.org/10.1080/02564602.2017.1293570.

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38

Mogas Recalde, Jordi, Ramon Palau, and Marian Márquez. "How classroom acoustics influence students and teachers: A systematic literature review." Journal of Technology and Science Education 11, no. 2 (April 27, 2021): 245. http://dx.doi.org/10.3926/jotse.1098.

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Acoustics in schools have been studied during years, but nowadays there are more possibilities than ever before to introduce improvements. This study presents a systematic literature review determining what acoustic parameters are present in classrooms and how they affect both teachers and students. Following the analysis, we put forward a two-block classification: the physical parameters of the sound or noise in the classroom and the consequences of the acoustics on the people in the classroom. Advances in the design of learning spaces and the use of technologies ranging from devices and green material to advanced automation systems make it possible to direct acoustic solutions toward smarter learning spaces. This review also highlights the acoustic parameters to consider in smart classrooms (noise, reverberation, speech transmission and speech clarity) and the main effects of acoustics on teachers and students. Some conclusions and recommendations are drawn, but more research is needed in terms of school improvement considering acoustics influence and smart classrooms possibilities.
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39

Goberman, Alexander M., and Carl Coelho. "Acoustic analysis of Parkinsonian speech I: Speech characteristics and L-Dopa therapy." NeuroRehabilitation 17, no. 3 (August 10, 2002): 237–46. http://dx.doi.org/10.3233/nre-2002-17310.

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40

Melle, Natalia, and Carlos Gallego. "Differential Diagnosis between Apraxia and Dysarthria Based on Acoustic Analysis." Spanish journal of psychology 15, no. 2 (July 2012): 495–504. http://dx.doi.org/10.5209/rev_sjop.2012.v15.n2.38860.

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Acoustic analysis provides objective quantitative measures of speech that enable a comprehensive and accurate understanding of motor disorders and complement the traditional measures. This paper aims to distinguish between normal and pathological speech, more specifically between apraxia of speech and spastic dysarthria in native Spanish speaking patients using acoustic parameters. Participants (4 aphasic with apraxia of speech, 4 with spastic dysarthria, and 15 without speech disorders) performed three different tasks: repeating the syllable sequence [pa-ta-ka], repeating the isolated syllable [pa] and repeating the vowel sequence [i-u]. The results showed that the normative values of motor control, in general, coincide with those obtained in previous research on native English speakers. They also show that damage to motor control processes results in a decrease in the rate of alternating and sequential movements and an increase in the inter-syllabic time for both types of movements. A subset of the acoustic parameters analyzed, those that measure motor planning processes, enable differentiation between normal population and apraxic and dysarthric patients, and between the latter. The differences between the pathological groups support the distinction between motor planning and motor programming as described by van der Merwe's model of sensorimotor processing (1997).
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41

Hirst, Daniel. "The analysis by synthesis of speech melody." Journal of Speech Sciences 1, no. 1 (July 1, 2011): 55–83. http://dx.doi.org/10.20396/joss.v1i1.15011.

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This paper describes the application of the analysis by synthesis paradigm to the melody of speech. Acomplete chain of processes is described from the acoustic analysis of fundamental frequency (f0), via thephonetic modelling of f0 using the Momel algorithm, to the surface phonological representation of thecurves using the INTSINT alphabet. Each step of the chain is designed as a reversible process which can beused to generate an acoustic output allowing an objective evaluation of the analysis. Finally, the currentimplementation of ProZed, a prosody editor for linguists, is described. It is argued that an explicit set ofmodelling tools like this will allow linguists to test different models of phonological structure which, it ishoped, will result in the availability of more and better data on a wide variety of languages.
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Nevler, Naomi, Sharon Ash, Corey McMillan, Lauren Elman, Leo McCluskey, David J. Irwin, Sunghye Cho, Mark Liberman, and Murray Grossman. "Automated analysis of natural speech in amyotrophic lateral sclerosis spectrum disorders." Neurology 95, no. 12 (July 16, 2020): e1629-e1639. http://dx.doi.org/10.1212/wnl.0000000000010366.

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ObjectiveWe implemented automated methods to analyze speech and evaluate the hypothesis that cognitive and motor factors impair prosody in partially distinct ways in patients with amyotrophic lateral sclerosis (ALS).MethodsWe recruited 213 participants, including 67 with ALS (44 with motor ALS, 23 with ALS and frontotemporal degeneration [FTD]), 33 healthy controls, and neurodegenerative reference groups with behavioral variant FTD (n = 90) and nonfluent/agrammatic primary progressive aphasia (n = 23). Digitized, semistructured speech samples obtained from picture descriptions were automatically segmented with a Speech Activity Detector; continuous speech segments were pitch-tracked; and duration measures for speech and silent pause segments were extracted. Acoustic measures were calculated, including fundamental frequency (f0) range, mean speech and pause segment durations, total speech duration, and pause rate (pause count per minute of speech). Group comparisons related performance on acoustic measures to clinical scales of cognitive and motor impairments and explored MRI cortical thinning in ALS and ALS-FTD.ResultsThe f0 range was significantly impaired in ALS spectrum disorders and was related to bulbar motor disease, and regression analyses related this to cortical thickness in primary motor cortex and perisylvian regions. Impaired speech and pause duration measures were related to the degree of cognitive impairment in ALS spectrum disorders, and regressions related duration measures to bilateral frontal opercula and left anterior insula.ConclusionAutomated analyses of acoustic speech properties dissociate motor and cognitive components of speech deficits in ALS spectrum disorders.
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Oliveira, Patrícia M., Francisco Cardoso, Débora P. Maia, Mauro César Q. Cunningham, Antonio Lúcio Teixeira Jr, and César Reis. "Acoustic analysis of prosody in Sydenham's chorea." Arquivos de Neuro-Psiquiatria 68, no. 5 (October 2010): 744–48. http://dx.doi.org/10.1590/s0004-282x2010000500013.

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There are few studies of language and speech in patients with Sydenham's chorea (SC). We have done an acoustic analysis of fundamental frequency (F0), duration and intensity of declarative and interrogative sentences made by 20 SC patients, 20 patients with rheumatic fever (RF) without chorea, and compared them with 20 healthy age-matched controls (CO). Each group included 12 females. We found that there is no difference between the RF and CO groups in all studied parameters. Patients with SC, however, presented with a speech characterized by decreased F0 range (difference between minimum and maximum F0), shorter duration of sentences, and higher intensity of the first syllable of sentences. The findings were not influenced by the nature of the sentences (i.e. , declarative or interrogative), but for all variables they were significantly more severe in males than females. In conclusion, we have demonstrated that patients with acute SC have an impairment of modulation of F0 and longer duration of emission of sentences, resulting in a monotone and slow speech. This pattern is similar to what has been described in other basal ganglia illnesses, such as Parkinson's disease, Huntington's disease and Wilson's disease.
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Chang, Ran Ran, Xiao Qing Yu, Ying Ying Yuan, and Wang Gen Wan. "Emotional Analysis and Synthesis of Human Voice Based on STRAIGHT." Applied Mechanics and Materials 536-537 (April 2014): 105–10. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.105.

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Speech synthesis is a hot research of artificial intelligence today, and urgent difficulty to overcome is how to make the machine more "emotional intelligence" for the human-computer interaction. With the STRAIGHT algorithm, this paper extracted the acoustic feature parameters of the speech signals and did statistical analysis, modified the characteristic parameters of the neutral sounds to synthesize emotional speeches, including happy, angry, frustration, then analyzed a frame of spectrum of synthetic emotional speeches through standard voices, voices added noise and voices de-nosing. The experimental results show that the method is feasible and the synthetic emotional speeches through voices de-nosing are better than voices added noise.
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Zhang, Yixin, Yoshitaka Nakajima, Kazuo Ueda, Takuya Kishida, and Gerard B. Remijn. "Comparison of Multivariate Analysis Methods as Applied to English Speech." Applied Sciences 10, no. 20 (October 12, 2020): 7076. http://dx.doi.org/10.3390/app10207076.

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A newly developed factor analysis, origin-shifted factor analysis, was compared with a normal factor analysis to analyze the spectral changes of English speech. Our first aim was to investigate whether these analyses would cause differences in the factor loadings and the extracted spectral-factor scores. The methods mainly differed in whether to use cepstral liftering and an origin shift. The results showed that three spectral factors were obtained in four main frequency bands, but neither the cepstral liftering nor the origin shift distorted the essential characteristics of the factors. This confirms that the origin-shifted factor analysis is more recommendable for future speech analyses, since it would reduce the generation of noise in resynthesized speech. Our second aim was to further identify acoustic correlates of English phonemes. Our data show for the first time that the distribution of obstruents in English speech constitutes an L-shape related to two spectral factors on the three-dimensional configuration. One factor had center loadings around 4100 Hz, while the other was bimodal with peaks around 300 Hz and 2300 Hz. This new finding validates the use of multivariate analyses to connect English phonology and speech acoustics.
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Al Mahmud, Nahyan, and Shahfida Amjad Munni. "Qualitative Analysis of PLP in LSTM for Bangla Speech Recognition." International journal of Multimedia & Its Applications 12, no. 5 (October 30, 2020): 1–8. http://dx.doi.org/10.5121/ijma.2020.12501.

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The performance of various acoustic feature extraction methods has been compared in this work using Long Short-Term Memory (LSTM) neural network in a Bangla speech recognition system. The acoustic features are a series of vectors that represents the speech signals. They can be classified in either words or sub word units such as phonemes. In this work, at first linear predictive coding (LPC) is used as acoustic vector extraction technique. LPC has been chosen due to its widespread popularity. Then other vector extraction techniques like Mel frequency cepstral coefficients (MFCC) and perceptual linear prediction (PLP) have also been used. These two methods closely resemble the human auditory system. These feature vectors are then trained using the LSTM neural network. Then the obtained models of different phonemes are compared with different statistical tools namely Bhattacharyya Distance and Mahalanobis Distance to investigate the nature of those acoustic features.
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47

de Boer, Janna, Alban Voppel, Frank Wijnen, and Iris Sommer. "T59. ACOUSTIC SPEECH MARKERS FOR SCHIZOPHRENIA." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S253—S254. http://dx.doi.org/10.1093/schbul/sbaa029.619.

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Abstract Background Clinicians routinely use impressions of speech as an element of mental status examination, including ‘pressured’ speech in mania and ‘monotone’ or ‘soft’ speech in depression or psychosis. In psychosis in particular, descriptions of speech are used to monitor (negative) symptom severity. Recent advances in computational linguistics have paved the way towards automated speech analyses as a biomarker for psychosis. In the present study, we assessed the diagnostic value of acoustic speech features in schizophrenia. We hypothesized that a classifier would be highly accurate (~ 80%) in classifying patients and healthy controls. Methods Natural speech samples were obtained from 86 patients with schizophrenia and 77 age and gender matched healthy controls through a semi-structured interview, using a set of neutral open-ended questions. Symptom severity was rated by consensus rating of two trained researchers, blinded to phonetic analysis, with the Positive And Negative Syndrome Scale (PANSS). Acoustic features were extracted with OpenSMILE, employing the Geneva Acoustic Minimalistic Parameter Set (GeMAPS), which comprises standardized analyses of pitch (F0), formants (F1, F2 and F3, i.e. acoustic resonance frequencies that indicate the position and movement of the articulatory muscles during speech production), speech quality, length of voiced and unvoiced regions. Speech features were fed into a linear kernel support vector machine (SVM) with leave-one-out cross-validation to assess their value for psychosis diagnosis. Results Demographic analyses revealed no differences between patients with schizophrenia and healthy controls in age or parental education. An automated machine-learning speech classifier reached an accuracy of 82.8% in classifying patients with schizophrenia and controls on speech features alone. Important features in the model were variation in loudness, spectral slope (i.e. the gradual decay in energy in high frequency speech sounds) and the amount of voiced regions (i.e. segments of the interview where the participant was speaking). PANSS positive, negative and general scores were significantly correlated with pitch, formant frequencies and length of voiced and unvoiced regions. Discussion This study demonstrates that an algorithm using quantified features of speech can objectively differentiate patients with schizophrenia from controls with high accuracy. Further validation in an independent sample is required. Employing standardized parameter sets ensures easy replication and comparison of analyses and can be used for cross linguistic studies. Although at an early stage, the field of clinical computational linguistics introduces a powerful tool for diagnosis and prognosis of psychosis and neuropsychiatric disorders in general. We consider this new diagnostic tool to be of high potential given its ease of acquirement, low costs and patient burden. For example, this tool could easily be implemented as a smartphone app to be used in treatment settings.
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48

Slavin, Dianne C., and Carole T. Ferrand. "Factor Analysis of Proficient Esophageal Speech: Toward a Multidimensional Model." Journal of Speech, Language, and Hearing Research 38, no. 6 (December 1995): 1224–31. http://dx.doi.org/10.1044/jshr.3806.1224.

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This study identified acoustic patterns in the speech samples of 26 esophageal speakers judged by experienced listeners to be highly proficient and intelligible. Tape-recorded readings were acoustically analyzed in terms of frequency, intensity, and duration variables. Application of two multidimensional statistical procedures, factor analysis and cluster analysis, revealed four distinctive acoustic profiles that captured all 26 subjects. The multidimensional model derived from these profiles maintains important individual differences in alaryngeal speech style.
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Hillenbrand, James M. "Acoustic Analysis of Voice: A Tutorial." Perspectives on Speech Science and Orofacial Disorders 21, no. 2 (October 2011): 31–43. http://dx.doi.org/10.1044/ssod21.2.31.

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This tutorial reviews acoustic methods that have been used to characterize vocal function. The most persuasive argument for the use of acoustic measures is that all of the information used by listeners to make judgments about speech is to be found in the acoustic signal. Acoustic methods have been used clinically to differentiate normal from abnormal voices, to aid in differential diagnosis, to evaluate the relative effectiveness of different treatment approaches, and to track progress in voice therapy. The measures discussed here focus on quantifying the degree of periodicity, the shape of the spectrum, and the range of vocal intensity.
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Miyazaki, Takeshi, Mitsunori Mizumachi, and Katsuyuki Niyada. "Acoustic Analysis of Breathy and Rough Voice Characterizing Elderly Speech." Journal of Advanced Computational Intelligence and Intelligent Informatics 14, no. 2 (March 20, 2010): 135–41. http://dx.doi.org/10.20965/jaciii.2010.p0135.

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This paper aims at investigating acoustic features, which can objectively explain breathiness and roughness of elderly speech, respectively. In this paper, acoustic analysis was carried out using word sequences, which were uttered by 153 male speakers in the age range of between 20 and 89 years old. Concerning the breathiness, we confirmed that elderly breathy voices caused energy lift in higher frequency region over 4 kHz in average power spectra during the stationary parts in the uttered vowels. Concerning roughness, we observed the slight fluctuations, which synchronized with vocal cord vibration, in amplitude spectra during stationary parts of vowels. Based on acoustic analysis results, we propose physical parameters for measuring breathiness and roughness, respectively. In this paper, listening tests were carried out to quantitatively give the subject degrees of breathiness and roughness, respectively. It was confirmed that the proposed physical parameters had correlation with each of subjective degrees. Relationships between age and acoustic characteristics of breathiness and roughness were investigated using the proposed parameters. It is confirmed that the degree of breathiness and roughness increased in proportion to age, especially in age ranges over 60 years old.
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