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Journal articles on the topic 'Speech waveforms'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

Milenkovic, Paul. "Least Mean Square Measures of Voice Perturbation." Journal of Speech, Language, and Hearing Research 30, no. 4 (1987): 529–38. http://dx.doi.org/10.1044/jshr.3004.529.

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A signal processing technique is described for measuring the jitter, shimmer, and signal-to-noise ratio of sustained vowels. The measures are derived from the least mean square fit of a waveform model to the digitized speech waveform. The speech waveform is digitized at an 8.3 kHz sampling rate, and an interpolation technique is used to improve the temporal resolution of the model fit. The ability of these procedures to measure low levels of perturbation is evaluated both on synthetic speech waveforms and on the speech recorded from subjects with normal voice characteristics.

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2

Coorman, Geert. "Speech synthesis using concatenation of speech waveforms." Journal of the Acoustical Society of America 124, no. 6 (2008): 3371. http://dx.doi.org/10.1121/1.3047443.

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3

Ferit Gigi, Ercan. "Speech Synthesis Using Concatenation Of Speech Waveforms." Journal of the Acoustical Society of America 129, no. 1 (2011): 545. http://dx.doi.org/10.1121/1.3554813.

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4

Coorman, Geert. "Speech synthesis using concatenation of speech waveforms." Journal of the Acoustical Society of America 116, no. 3 (2004): 1331. http://dx.doi.org/10.1121/1.1809938.

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5

Xiong, Yan, Fang Xu, Qiang Chen, and Jun Zhang. "Speech Enhancement Using Heterogeneous Information." International Journal of Grid and High Performance Computing 10, no. 3 (2018): 46–59. http://dx.doi.org/10.4018/ijghpc.2018070104.

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This article describes how to use heterogeneous information in speech enhancement. In most of the current speech enhancement systems, clean speeches are recovered only from the signals collected by acoustic microphones, which will be greatly affected by the acoustic noises. However, heterogeneous information from different kinds of sensors, which is usually called the “multi-stream,” are seldom used in speech enhancement because the speech waveforms cannot be recovered from the signals provided by many kinds of sensors. In this article, the authors propose a new model-based multi-stream speech

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6

Kleijn, W. B. "Encoding speech using prototype waveforms." IEEE Transactions on Speech and Audio Processing 1, no. 4 (1993): 386–99. http://dx.doi.org/10.1109/89.242484.

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7

Maddieson, Ian. "Commentary on ‘Reading waveforms’." Journal of the International Phonetic Association 21, no. 2 (1991): 89–91. http://dx.doi.org/10.1017/s0025100300004436.

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The previous issue of the Journal contained a discussion by Peter Ladefoged about interpreting the information in a speech waveform (JIPA, 21, 32–34), noting that examination of waveforms displays is becoming commonplace with the easy availability of personal computer tools for digitizing and editing. As Ladefoged noted:“Several aspects of sounds are clearly distinguishable from the waveforms of a phrase. Stop closures are very evident, as are differences between voiced sounds which have repetitive waveforms and voiceless sounds which do not. Differences in amplitude can be used to distinguish

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8

Yohanes, Banu W. "Linear Prediction and Long Term Predictor Analysis and Synthesis." Techné : Jurnal Ilmiah Elektroteknika 16, no. 01 (2017): 49–58. http://dx.doi.org/10.31358/techne.v16i01.158.

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Spectral analysis may not provide an accurate description of speech articulation. This article presents an experimental setup of representing speech waveform directly in terms of timevarying parameters. It is related to the transfer function of the vocal tract. Linear Prediction, Long Term Predictor Analysis, and Synthesis filters are designed and implemented, as well as the theory behind introduced. The workflows of the filters are explained by detailed and codes of those filters. Original waveform files are framed with Hamming window and for each frames the filters are applied, and the recon

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9

Arda, Betul, Daniel Rudoy, and Patrick J. Wolfe. "Testing for periodicity in speech waveforms." Journal of the Acoustical Society of America 125, no. 4 (2009): 2699. http://dx.doi.org/10.1121/1.4784326.

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10

Terzopoulos, D. "Co-occurrence analysis of speech waveforms." IEEE Transactions on Acoustics, Speech, and Signal Processing 33, no. 1 (1985): 5–30. http://dx.doi.org/10.1109/tassp.1985.1164511.

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11

Latypov, R. Kh, R. R. Nigmatullin, and E. L. Stolov. "Classification of speech files by waveforms." Lobachevskii Journal of Mathematics 36, no. 4 (2015): 496–502. http://dx.doi.org/10.1134/s1995080215040265.

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12

Verneuil, Andrew, Bruce R. Gerratt, David A. Berry, Ming Ye, Jody Kreiman, and Gerald S. Berke. "Modeling Measured Glottal Volume Velocity Waveforms." Annals of Otology, Rhinology & Laryngology 112, no. 2 (2003): 120–31. http://dx.doi.org/10.1177/000348940311200204.

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The source-filter theory of speech production describes a glottal energy source (volume velocity waveform) that is filtered by the vocal tract and radiates from the mouth as phonation. The characteristics of the volume velocity waveform, the source that drives phonation, have been estimated, but never directly measured at the glottis. To accomplish this measurement, constant temperature anemometer probes were used in an in vivo canine constant pressure model of phonation. A 3-probe array was positioned supraglottically, and an endoscopic camera was positioned subglottically. Simultaneous recor

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13

Das, Amitava, and Eddie L. T. Choy. "Synthesis of speech from pitch prototype waveforms by time-synchronous waveform interpolation." Journal of the Acoustical Society of America 117, no. 3 (2005): 993. http://dx.doi.org/10.1121/1.1896665.

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14

Fox, Lisa G., and Susan D. Dalebout. "Use of the Median Method to Enhance Detection of the Mismatch Negativity in the Responses of Individual Listeners." Journal of the American Academy of Audiology 13, no. 02 (2002): 083–92. http://dx.doi.org/10.1055/s-0040-1715951.

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The median method was evaluated as an alternative way of expressing the mismatch negativity (MMN). Traditionally, signal averaging has been used to extract these event-related potentials from unwanted background noise. However, mean values are biased by unrejected artifact that skews the relatively small distribution of values on which the MMN is based. Because the median is a more valid measure of central tendency in asymmetric distributions, it may describe MMN data more accurately. Better representation of the signal in the median waveform might enhance detection of the MMN in the responses

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15

Sprague, Richard P. "Compression of stored waveforms for artificial speech." Journal of the Acoustical Society of America 90, no. 4 (1991): 2220. http://dx.doi.org/10.1121/1.401581.

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16

Payton, Karen L., and Louis D. Braida. "A method to determine the speech transmission index from speech waveforms." Journal of the Acoustical Society of America 106, no. 6 (1999): 3637–48. http://dx.doi.org/10.1121/1.428216.

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17

Wang, Jiaquan, Qijun Huang, Qiming Ma, et al. "Classification of VLF/LF Lightning Signals Using Sensors and Deep Learning Methods." Sensors 20, no. 4 (2020): 1030. http://dx.doi.org/10.3390/s20041030.

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Lightning waveform plays an important role in lightning observation, location, and lightning disaster investigation. Based on a large amount of lightning waveform data provided by existing real-time very low frequency/low frequency (VLF/LF) lightning waveform acquisition equipment, an automatic and accurate lightning waveform classification method becomes extremely important. With the widespread application of deep learning in image and speech recognition, it becomes possible to use deep learning to classify lightning waveforms. In this study, 50,000 lightning waveform samples were collected.

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18

Chen, Jie, and Jing Chen. "The Operation of Cool Edit Pro in Corpus-Based Spoken Language." Advanced Materials Research 694-697 (May 2013): 2383–87. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.2383.

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Corpus refers to the database of language materials. Cool Edit Pro is a media edit software. This paper explores how to construct spoken language corpus, how to use cool edit pro 2 to make sound wave contrast and give the experimenters an intuitive observation from their own speech waveforms. The key is to offer the obvious waveforms contrast among the sampling waveform of the native speaker, the original and unmodified one of the experimenter and the new waveform of the experimenter after modifications and teachers instructions, which makes the oral autonomic learning more possible and scient

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19

Ng, C. S., and P. H. Milenkovic. "Unstable covariance LPC solutions from nonstationary speech waveforms." IEEE Transactions on Acoustics, Speech, and Signal Processing 37, no. 5 (1989): 651–54. http://dx.doi.org/10.1109/29.17557.

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20

Breen, Andrew Paul. "Synthesising speech by converting phonemes to digital waveforms." Journal of the Acoustical Society of America 115, no. 4 (2004): 1401. http://dx.doi.org/10.1121/1.1738269.

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21

Kang, George S., and Lawrence J. Fransen. "Method and apparatus for generating modified speech from pitch-synchronous segmented speech waveforms." Journal of the Acoustical Society of America 107, no. 6 (2000): 2950. http://dx.doi.org/10.1121/1.429368.

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22

Bergstrom, Chad Scott. "Method and apparatus for synthesis of speech excitation waveforms." Journal of the Acoustical Society of America 104, no. 5 (1998): 2556. http://dx.doi.org/10.1121/1.423784.

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23

McKinley, Paula S., Peter A. Shapiro, Emilia Bagiella, et al. "Deriving heart period variability from blood pressure waveforms." Journal of Applied Physiology 95, no. 4 (2003): 1431–38. http://dx.doi.org/10.1152/japplphysiol.01110.2002.

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International standards for calculating heart period variability (HPV) from a series of R-wave intervals (R-R) in an electrocardiographic (ECG) recording have been widely accepted. It is possible, and potentially useful in various settings, to use systolic blood pressure waveform intervals to estimate HPV, but the validity of HPV derived from blood pressure (BP) waveforms has not been established. To test the reliability between BP- and ECG-derived HPV indexes, we evaluated data from 234 healthy adults in four studies of HPV reactivity to stress. Study conditions included resting baseline, ari

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24

Freyman, Richard L., G. Patrick Nerbonne, and Heather A. Cote. "Effect of Consonant-Vowel Ratio Modification on Amplitude Envelope Cues for Consonant Recognition." Journal of Speech, Language, and Hearing Research 34, no. 2 (1991): 415–26. http://dx.doi.org/10.1044/jshr.3402.415.

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This investigation examined the degree to which modification of the consonant-vowel (C-V) intensity ratio affected consonant recognition under conditions in which listeners were forced to rely more heavily on waveform envelope cues than on spectral cues. The stimuli were 22 vowel-consonant-vowel utterances, which had been mixed at six different signal-to-noise ratios with white noise that had been modulated by the speech waveform envelope. The resulting waveforms preserved the gross speech envelope shape, but spectral cues were limited by the white-noise masking. In a second stimulus set, the

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25

Tucker, Denise A., Susan Dietrich, Stacy Harris, and Sarah Pelletier. "Effects of Stimulus Rate and Gender on the Auditory Middle Latency Response." Journal of the American Academy of Audiology 13, no. 03 (2002): 146–53. http://dx.doi.org/10.1055/s-0040-1715956.

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The effects of stimulus rate and gender on the auditory middle latency response (AMLR) waveforms were examined in 20 young adult male and female subjects. Four different repetition rates were presented to subjects (1.1/sec, 4.1/sec, 7.7/sec, and 11.3/sec). Stimulus repetition rate had a significant effect on Pa latency, Pa amplitude, and Pb amplitude. Pa and Pb amplitudes decreased with increasing the stimulus rate, and Pa latency significantly increased with increasing the stimulus rate. No significant differences were seen on Pb latency or site of recording. Gender had a significant effect o

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26

Sharma, Pranav, Puneet Kochar, Priti Soin, and Steven Cohen. "Bisystolic Vertebral Artery: Critical Finding or can be Ignored?" Journal of Clinical Imaging Science 9 (January 31, 2019): 2. http://dx.doi.org/10.4103/jcis.jcis_80_18.

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The carotid Doppler imaging findings in three adults presenting with vertigo, transient speech difficulty and for cardiac prebypass graft surgery revealing two systolic peaks in one of the vertebral arteries. In presteal situations, vertebral artery waveform shows two systolic peaks with sharp first and rounded second systolic peak or two systolic peaks with a deep cleft between the two peaks with antegrade flow. With increase in stenosis to more than 80% there is bidirectional flow and later flow reversal. We discuss the types of presteal vertebral artery waveforms, its clinical implications

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27

Neel, Amy T. "Using Acoustic Phonetics in Clinical Practice." Perspectives on Speech Science and Orofacial Disorders 20, no. 1 (2010): 14–24. http://dx.doi.org/10.1044/ssod20.1.14.

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Acoustic phonetics deals with the physical aspects of speech sounds associated with the production and perception of speech. Acoustic measurement techniques can be used by speech-language pathologists to assess and treat a variety of speech disorders. In this article, we will review the source-filter theory of speech production, acoustic theory of vowels, and acoustic properties of consonants. We will examine how visual displays of acoustic information in the form of waveforms, amplitude spectra, and spectrograms can be used to analyze aspects of speech that might be difficult to hear and serv

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28

Palmer, Shannon B., and Frank E. Musiek. "N1-P2 Recordings to Gaps in Broadband Noise." Journal of the American Academy of Audiology 24, no. 01 (2013): 037–45. http://dx.doi.org/10.3766/jaaa.24.1.5.

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Background: Normal temporal processing is important for the perception of speech in quiet and in difficult listening situations. Temporal resolution is commonly measured using a behavioral gap detection task, where the patient or subject must participate in the evaluation process. This is difficult to achieve with subjects who cannot reliably complete a behavioral test. However, recent research has investigated the use of evoked potential measures to evaluate gap detection. Purpose: The purpose of the current study was to record N1-P2 responses to gaps in broadband noise in normal hearing youn

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29

Hamon, Christian. "Processing device for speech synthesis by addition of overlapping waveforms." Journal of the Acoustical Society of America 101, no. 4 (1997): 1766. http://dx.doi.org/10.1121/1.418194.

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30

Wohlert, Amy B. "Event-Related Brain Potentials Preceding Speech and Nonspeech Oral Movements of Varying Complexity." Journal of Speech, Language, and Hearing Research 36, no. 5 (1993): 897–905. http://dx.doi.org/10.1044/jshr.3605.897.

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Cortical preparation for movement is reflected in the readiness potential (RP) waveform preceding voluntary limb movements. In the case of oral movements, the RP may be affected by the complexity or linguistic nature of the tasks. In this experiment, EEG potentials before a nonspeech task (lip pursing), a speech-like task (lip rounding), and single word production were recorded from scalp electrodes placed at the cranial vertex (Cz) and over the left and right motor strips (C3′ and C4′). Seven right-handed female subjects produced at least 70 repetitions of the three tasks, in each of five rep

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31

Rothenberg, Martin, and James J. Mahshie. "Monitoring Vocal Fold Abduction through Vocal Fold Contact Area." Journal of Speech, Language, and Hearing Research 31, no. 3 (1988): 338–51. http://dx.doi.org/10.1044/jshr.3103.338.

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A number of commercial devices for measuring the transverse electrical conductance of the thyroid cartilage produce waveforms that can be useful for monitoring movements within the larynx during voice production, especially movements that are closely related to the time-variation of the contact between the vocal folds as they vibrate. This paper compares the various approaches that can be used to apply such a device, usually referred to as an electroglottograph, to the problem of monitoring the time-variation of vocal fold abduction and adduction during voiced speech. One method, in which a me

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32

Zhao, Yong. "Refining of segmental boundaries in speech waveforms using contextual-dependent models." Journal of the Acoustical Society of America 128, no. 6 (2010): 3827. http://dx.doi.org/10.1121/1.3544446.

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33

Gibson, J. "Digital coding of waveforms: Priciples and application to speech and video." IEEE Transactions on Acoustics, Speech, and Signal Processing 33, no. 6 (1985): 1636–37. http://dx.doi.org/10.1109/tassp.1985.1164724.

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34

Bergstrom, Chad S. "Method and apparatus for characterization and reconstruction of speech excitation waveforms." Journal of the Acoustical Society of America 102, no. 5 (1997): 2481. http://dx.doi.org/10.1121/1.420376.

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35

Gibson, J. D. "Digital coding of waveforms: Principles and applications to speech and video." Proceedings of the IEEE 75, no. 4 (1987): 526–27. http://dx.doi.org/10.1109/proc.1987.13765.

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36

Jayant, N. S., and P. Noll. "Digital coding of waveforms. Principles and applications to speech and video." Signal Processing 9, no. 2 (1985): 139–40. http://dx.doi.org/10.1016/0165-1684(85)90053-2.

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37

Glista, Danielle, Vijayalakshmi Easwar, David W. Purcell, and Susan Scollie. "A Pilot Study on Cortical Auditory Evoked Potentials in Children: Aided CAEPs Reflect Improved High-Frequency Audibility with Frequency Compression Hearing Aid Technology." International Journal of Otolaryngology 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/982894.

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Background. This study investigated whether cortical auditory evoked potentials (CAEPs) could reliably be recorded and interpreted using clinical testing equipment, to assess the effects of hearing aid technology on the CAEP.Methods. Fifteen normal hearing (NH) and five hearing impaired (HI) children were included in the study. NH children were tested unaided; HI children were tested while wearing hearing aids. CAEPs were evoked with tone bursts presented at a suprathreshold level. Presence/absence of CAEPs was established based on agreement between two independent raters.Results. Present wave

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38

Beyreuther, M., and J. Wassermann. "Hidden semi-Markov Model based earthquake classification system using Weighted Finite-State Transducers." Nonlinear Processes in Geophysics 18, no. 1 (2011): 81–89. http://dx.doi.org/10.5194/npg-18-81-2011.

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Abstract. Automatic earthquake detection and classification is required for efficient analysis of large seismic datasets. Such techniques are particularly important now because access to measures of ground motion is nearly unlimited and the target waveforms (earthquakes) are often hard to detect and classify. Here, we propose to use models from speech synthesis which extend the double stochastic models from speech recognition by integrating a more realistic duration of the target waveforms. The method, which has general applicability, is applied to earthquake detection and classification. Firs

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39

Howard, Mary F., and David Poeppel. "Discrimination of Speech Stimuli Based on Neuronal Response Phase Patterns Depends on Acoustics But Not Comprehension." Journal of Neurophysiology 104, no. 5 (2010): 2500–2511. http://dx.doi.org/10.1152/jn.00251.2010.

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Speech stimuli give rise to neural activity in the listener that can be observed as waveforms using magnetoencephalography. Although waveforms vary greatly from trial to trial due to activity unrelated to the stimulus, it has been demonstrated that spoken sentences can be discriminated based on theta-band (3–7 Hz) phase patterns in single-trial response waveforms. Furthermore, manipulations of the speech signal envelope and fine structure that reduced intelligibility were found to produce correlated reductions in discrimination performance, suggesting a relationship between theta-band phase pa

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40

Rosen, Stuart, John Walliker, Judith A. Brimacombe, and Bradly J. Edgerton. "Prosodic and Segmental Aspects of Speech Perception with the House/3M Single-Channel Implant." Journal of Speech, Language, and Hearing Research 32, no. 1 (1989): 93–111. http://dx.doi.org/10.1044/jshr.3201.93.

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Four adult users of the House/3M single-channel cochlear implant were tested for their ability to label question and statement intonation contours (by auditory means alone) and to identify a set of 12 intervocalic consonants (with and without lipreading). Nineteen of 20 scores obtained on the question/statement task were significantly better than chance. Simplifying the stimulating waveform so as to signal fundamental frequency alone sometimes led to an improvement in performance. In consonant identification, lipreading alone scores were always far inferior to those obtained by lipreading with

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41

Tür, Gökhan, Dilek Hakkani-Tür, Andreas Stolcke, and Elizabeth Shriberg. "Integrating Prosodic and Lexical Cues for Automatic Topic Segmentation." Computational Linguistics 27, no. 1 (2001): 31–57. http://dx.doi.org/10.1162/089120101300346796.

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We present a probabilistic model that uses both prosodic and lexical cues for the automatic segmentation of speech into topically coherent units. We propose two methods for combining lexical and prosodic information using hidden Markov models and decision trees. Lexical information is obtained from a speech recognizer, and prosodic features are extracted automatically from speech waveforms. We evaluate our approach on the Broadcast News corpus, using the DARPA-TDT evaluation metrics. Results show that the prosodic model alone is competitive with word-based segmentation methods. Furthermore, we

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42

Wohlert, Amy B., and Anne Smith. "Developmental Change in Variability of Lip Muscle Activity During Speech." Journal of Speech, Language, and Hearing Research 45, no. 6 (2002): 1077–87. http://dx.doi.org/10.1044/1092-4388(2002/086).

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Compared to adults, children's speech production measures sometimes show higher trial-to-trial variability in both kinematic and acoustic analyses. A reasonable hypothesis is that this variability reflects variations in neural drive to muscles as the developing system explores different solutions to achieving vocal tract goals. We investigated that hypothesis in the present study by analyzing EMG waveforms produced across repetitions of a phrase spoken by 7-year-olds, 12-year-olds, and young adults. The EMG waveforms recorded via surface electrodes at upper lip sites were clearly modulated in

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43

Stokes, Michael A. "Identification of vowels based on visual cues within raw complex speech waveforms." Journal of the Acoustical Society of America 99, no. 4 (1996): 2589–603. http://dx.doi.org/10.1121/1.415250.

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44

Zhang, Fawen, Chelsea Benson, and Steven J. Cahn. "Cortical Encoding of Timbre Changes in Cochlear Implant Users." Journal of the American Academy of Audiology 24, no. 01 (2013): 046–58. http://dx.doi.org/10.3766/jaaa.24.1.6.

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Background: Most cochlear implant (CI) users describe music as a noise-like and unpleasant sound. Using behavioral tests, most prior studies have shown that perception of pitch-based melody and timbre is poor in CI users. Purpose: This article will focus on cortical encoding of timbre changes in CI users, which may allow us to find solutions to further improve CI benefits. Furthermore, the value of using objective measures to reveal neural encoding of timbre changes may be reflected in this study. Research Design: A case-control study of the mismatch negativity (MMN) using electrophysiological

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45

Zhang, Ming. "Using Concha Electrodes to Measure Cochlear Microphonic Waveforms and Auditory Brainstem Responses." Trends in Amplification 14, no. 4 (2010): 211–17. http://dx.doi.org/10.1177/1084713810388811.

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46

Painter, Colin, John M. Fredrickson, Timothy Kaiser, and Roanne Karzon. "Human Speech Development for an Implantable Artificial Larynx." Annals of Otology, Rhinology & Laryngology 96, no. 5 (1987): 573–77. http://dx.doi.org/10.1177/000348948709600519.

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An electromagnetic artificial larynx was implanted in two volunteer laryngectomees. Both patients were able to communicate well, but the voice quality still needed improving. Therefore, in this investigation, listener judgments were obtained of 22 different sound sources with a view to incorporating the preferred speech sound in a new version of the device. Electroglottograms were used as sound sources in a speech synthesizer and sentences were produced with different voice qualities for judgmental tests. The results of the listening tests showed a distinct preference for waveforms correspondi

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47

Alku, Paavo, Erkki Vilkman, and Anne-Maria Laukkanen. "Parameterization of the Voice Source by Combining Spectral Decay and Amplitude Features of the Glottal Flow." Journal of Speech, Language, and Hearing Research 41, no. 5 (1998): 990–1002. http://dx.doi.org/10.1044/jslhr.4105.990.

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A new method is presented for the parameterization of glottal volume velocity waveforms that have been estimated by inverse filtering acoustic speech pressure signals. The new technique, Parameter for Spectral and Amplitude Features of the Glottal Flow (PSA), combines two features of voice production, the AC value and the spectral decay of the glottal flow, both of which contribute to changes in vocal loudness. PSA yields a single parameter that characterizes the glottal flow in different loudness conditions. By analyzing voices of 8 speakers it was shown that the new parameter correlates stro

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48

Foti, Enzo. "Method of speech synthesis by means of concentration and partial overlapping of waveforms." Journal of the Acoustical Society of America 105, no. 2 (1999): 587. http://dx.doi.org/10.1121/1.427008.

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49

Grant, P. M. "Book review: Digital Coding of Waveforms—Principles and Applications to Speech and Video." IEE Proceedings F Communications, Radar and Signal Processing 132, no. 3 (1985): 186. http://dx.doi.org/10.1049/ip-f-1.1985.0041.

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50

Rothenberg, Martin. "Correcting Low-Frequency Phase Distortion in Electroglottograph Waveforms." Journal of Voice 16, no. 1 (2002): 32–36. http://dx.doi.org/10.1016/s0892-1997(02)00069-3.

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