DOCSLIB.ORG

This Thesis Has Been Approved by the Honors Tutorial College and The

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
This Thesis Has Been Approved by the Honors Tutorial College and The This thesis has been approved by The Honors Tutorial College and the Department of Communication Sciences & Disorders Dr. Li Xu Professor, Communication Sciences & Disorders Thesis Advisor Dr. Chao-Yang Lee Professor, Communication Sciences & Disorders Director of Studies, Communication Sciences & Disorders Dr. Donal Skinner Dean, Honors Tutorial College 2 PERCEPTION OF SPECTRALLY-DEGRADED, FOREIGN-ACCENTED SPEECH A Thesis Presented to The Honors Tutorial College Ohio University In Partial Fulfillment of the Requirements for Graduation from the Honors Tutorial College with the degree of Bachelor of Science in Communication Sciences & Disorders By Jenna Barrett April 2021 3 Introduction Background on Speech Perception Speech perception is an incredible and complicated process that allows us to hear, interpret, and understand speech sounds. It begins with a speech signal. Most of us understand speech as a string of letters which make up words, which make up sentences, which go on to form even larger elements of language. Physically, however, speech is an acoustic wave. This complex wave is made up of numerous sounds that run together and occasionally overlap, just as they do in words and sentences. The smallest units of sound are known as phonemes. When an acoustic wave reaches the ear, vibrations pass through the hearing structures and stimulate the auditory nerve. These nerve impulses are processed by the brain and integrated with previous knowledge of sound to allow for the comprehension of speech (Urbas, 2019). Within the nervous system, there are specialized mechanisms for processing speech. This is evidenced by experiments demonstrating that phonemes can be perceived at rates seven times faster than that of nonspeech sounds. What is perhaps even more impressive is the flexibility of this system. Humans can easily understand speech in their native language, often regardless of speech rate, voice, pitch, accent, loudness, or signal distortion. Even though the acoustic signal may be changed or distorted in many of these cases, the nervous system is able to rapidly adjust and compensate for these variations. This is known as perceptual constancy (Urbas, 2019). There are two main types of speech processing theories involved in perception: bottom-up processing and top-down processing (Figure 1). Bottom-up processing refers to using the simplest elements of an acoustic wave to guide more complex perception. 4 Within the wave, there are acoustic cues to phonemes, which can be combined into larger and larger speech components. Top-down processing is essentially the opposite. Complex linguistic knowledge, including context clues and sentence predictability, are used to anticipate speech. Both types of processing are necessary for speech perception. For example, in one study, researchers presented participants with a pair of words where the initial sound was a mixture of the /d/ and /t/ American English phonemes. In one instance, the phoneme made a nonsense word (drash) and in the other instance, the phoneme made a real word (trash). Participants were more likely to perceive the phoneme that created a real word (Austermann and Yamada, 2009). This is an example of the combination of processing techniques. Bottom-up processing would inform participants that the acoustic signal contained a phoneme similar to either /d/ or /t/, but top-down processing would allow participants to use previous linguistic knowledge to choose the phoneme that produced a real word. Figure 1. The figure above describes the interaction between top-down and bottom-up processing in the perception of a speech stimulus. The basic information derived from the acoustic wave as well as higher-level contextual information are important for speech perception (Austermann and Yamada, 2009). 5 In research based on non-tonal languages, it was proposed that bottom-up and top-down processing occurred in series, with application of the acoustic signal coming before the use of more complex linguistic knowledge. However, in recent research on tonal languages, it was found that both types of processing were present in early and late stages of processing. Researchers used event-related potentials (ERPs) to track the use of bottom-up and top-down processing in lexical tone perception. Based on the results, a parallel lexical tone processing model was proposed (Shuai and Gong, 2014). This research raises questions as to the different types of processing that may occur in native speakers of a language (L1) and second language learners (L2) when presented with speech that contains acoustic-phonetic deviations. The Normal Hearing Mechanism The hearing mechanism is an integral component of speech perception. In a normal hearing individual, the hearing process begins with sound. When an object vibrates, the pressure causes particles in the surrounding medium to move, creating a sound wave. This sound wave is funneled into the ear canal, causing the tympanic membrane to vibrate. In the middle ear, these vibrations are passed to three small ossicles known as the malleus, incus, and stapes. These bones vibrate in sequence and function to correct the impedance mismatch, or loss of sound energy, that occurs when traveling from an air to fluid medium. The mechanical vibrations from the ossicles are then transferred to the fluid-filled cochlea of the inner ear. The cochlea contains three membranes: Reissner’s membrane, the basilar membrane, and the tectorial membrane. The basilar membrane is organized tonotopically, meaning different areas of the 6 membrane respond to different frequencies. In the case of the basilar membrane, the basal portion is stimulated by higher frequencies and the apical portion is stimulated by lower frequencies. On the basilar membrane lies the organ of Corti, which contains sensory hair cells of hearing. Ultimately, the inner hair cells are responsible for the neural impulse that travels to the brain. There are three fluid-filled passages within the cochlea containing either perilymph or endolymph. Perilymph fills the scala vestibuli and scala tympani, the two chambers separated by the basilar membrane. Perilymph is rich in sodium ions. In contrast, endolymph fills the scala media, which is the chamber between the scala vestibuli and scala tympani, also known as the cochlear duct. Endolymph is rich in potassium ions. Inside the organ of Corti, inner hair cells are grouped in a single row, and each hair cell is linked to about ten nerve cells. These inner hair cells consist of a main body and thin stereocilia that stick out of the basilar membrane. Fluid vibrations within the cochlea cause stereocilia of hair cells in specific portions of the basilar membrane to bend. This bending opens up ion channels between the stereocilia and hair cells, altering the concentration of sodium and potassium ions in the nerve cell. In response, potassium rushes into the hair cells, depolarization of the hair cell occurs, and neurotransmitters (glutamate) are released from the bottom of the hair cells. The auditory nerves pick up the neurotransmitters and generate action potentials (Niparko, 2000). These electrical impulses are transmitted to the brain via the auditory nerve. The diagram below (Figure 2) illustrates this hearing process up to the cochlear level. 7 Figure 2. The figure above shows the anatomical structures involved in the mechanism of hearing. Sound waves enter the ear canal and cause the tympanic membrane to vibrate. These vibrations are amplified by the ossicles of the middle ear and transferred to the inner ear. Fluid vibrations in the cochlea cause hair cells to bend, creating electric potentials that stimulate the auditory nerve and create the perception of sound (Hawkins, 2020). Beyond the cochlea, the neural impulse must be transmitted from the cochlear nerve to the auditory cortex for identification and perception. Information from the cochlea follows the auditory pathway, which consists of roughly 4 sequential areas in the brain that work to decode the signal. The pathway begins with the cochleo-vestibular nerve. Recall that electrical impulses travel here via the auditory nerves that synapse with the hair cells in the cochlea. From the cochleo-vestibular nerve, the impulses travel to the cochlear nuclei of the brain stem where information on duration, intensity, and frequency of the signal is deciphered. Next, a neuron carries this information to the superior olivary complex of the brainstem. It is important to note that, while both brain hemispheres process sound stimuli from both ears, much of the information from the stimuli passes to the contralateral side at this junction. The signal then travels to the inferior colliculus of the brainstem. Both the superior olivary complex and inferior colliculus work to integrate information from both ears and determine sound lateralization and localization. A fourth 8 neuron then carries the signal up to the medial geniculate body of the thalamus, which functions to focus auditory attention and prepare a response to the sound signal. The last stop is the auditory cortex in the temporal lobe; here, the message of the signal is received and translated. Similar to the basilar membrane, the auditory cortex is organized tonotopically, with certain neurons tuned to specific frequencies; this allows for time and frequency information to be decoded. In addition, the primary auditory cortex is involved in identifying the sound, employing memory, and, if necessary, generating a response (Pujol, 2020). Information from the
Load more

Recommended publications
  • Decoding Articulatory Features from Fmri Responses in Dorsal Speech Regions
    The Journal of Neuroscience, November 11, 2015 • 35(45):15015–15025 • 15015 Behavioral/Cognitive Decoding Articulatory Features from fMRI Responses in Dorsal Speech Regions Joao M. Correia, Bernadette M.B. Jansma, and Milene Bonte Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, and Maastricht Brain Imaging Center, 6229 EV Maastricht, The Netherlands The brain’s circuitry for perceiving and producing speech may show a notable level of overlap that is crucial for normal development and behavior. The extent to which sensorimotor integration plays a role in speech perception remains highly controversial, however. Meth- odological constraints related to experimental designs and analysis methods have so far prevented the disentanglement of neural responses to acoustic versus articulatory speech features. Using a passive listening paradigm and multivariate decoding of single-trial fMRIresponsestospokensyllables,weinvestigatedbrain-basedgeneralizationofarticulatoryfeatures(placeandmannerofarticulation, and voicing) beyond their acoustic (surface) form in adult human listeners. For example, we trained a classifier to discriminate place of articulation within stop syllables (e.g., /pa/ vs /ta/) and tested whether this training generalizes to fricatives (e.g., /fa/ vs /sa/). This novel approach revealed generalization of place and manner of articulation at multiple cortical levels within the dorsal auditory pathway, including auditory, sensorimotor, motor, and somatosensory regions, suggesting
    [Show full text]
  • Sound and the Ear Chapter 2
    © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION Chapter© Jones & Bartlett 2 Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION Sound and the Ear © Jones Karen &J. Kushla,Bartlett ScD, Learning, CCC-A, FAAA LLC © Jones & Bartlett Learning, LLC Lecturer NOT School FOR of SALE Communication OR DISTRIBUTION Disorders and Deafness NOT FOR SALE OR DISTRIBUTION Kean University © Jones & Bartlett Key Learning, Terms LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR Acceleration DISTRIBUTION Incus NOT FOR SALE OR Saccule DISTRIBUTION Acoustics Inertia Scala media Auditory labyrinth Inner hair cells Scala tympani Basilar membrane Linear scale Scala vestibuli Bel Logarithmic scale Semicircular canals Boyle’s law Malleus Sensorineural hearing loss Broca’s area © Jones & Bartlett Mass Learning, LLC Simple harmonic© Jones motion (SHM) & Bartlett Learning, LLC Brownian motion Membranous labyrinth Sound Cochlea NOT FOR SALE OR Mixed DISTRIBUTION hearing loss Stapedius muscleNOT FOR SALE OR DISTRIBUTION Compression Organ of Corti Stapes Condensation Osseous labyrinth Tectorial membrane Conductive hearing loss Ossicular chain Tensor tympani muscle Decibel (dB) Ossicles Tonotopic organization © Jones Decibel & hearing Bartlett level (dB Learning, HL) LLC Outer ear © Jones Transducer & Bartlett Learning, LLC Decibel sensation level (dB SL) Outer hair cells Traveling wave theory NOT Decibel FOR sound SALE pressure OR level DISTRIBUTION
    [Show full text]
  • SIRT1 Protects Cochlear Hair Cell and Delays Age-Related Hearing Loss Via Autophagy
    Neurobiology of Aging 80 (2019) 127e137 Contents lists available at ScienceDirect Neurobiology of Aging journal homepage: www.elsevier.com/locate/neuaging SIRT1 protects cochlear hair cell and delays age-related hearing loss via autophagy Jiaqi Pang a,b,c,d,1, Hao Xiong a,b,e,1, Yongkang Ou a,b,e, Haidi Yang a,b,e, Yaodong Xu a,b, Suijun Chen a,b,e, Lan Lai a,b,c, Yongyi Ye a,f, Zhongwu Su a,b, Hanqing Lin a,b, Qiuhong Huang a,b,e, Xiaoding Xu c,d,*, Yiqing Zheng a,b,e,** a Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou China b Institute of Hearing and Speech-Language Science, Sun Yat-sen University, Guangzhou, China c Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China d RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China e Department of Hearing and Speech Science, Xinhua College, Sun Yat-sen University, Guangzhou, China f School of Public Health, Sun Yat-Sen University, Guangzhou, China article info abstract Article history: Age-related hearing loss (AHL) is typically caused by the irreversible death of hair cells (HCs). Autophagy Received 10 January 2019 is a constitutive pathway to strengthen cell survival under normal or stress condition. Our previous work Received in revised form 29 March 2019 suggested that impaired autophagy played an important role in the development of AHL in C57BL/6 mice, Accepted 4 April 2019 although the underlying mechanism of autophagy in AHL still needs to be investigated.
    [Show full text]
  • Download Article (PDF)
    Libri Phonetica 1999;56:105–107 = Part I, ‘Introduction’, includes a single Winifred Strange chapter written by the editor. It is an Speech Perception and Linguistic excellent historical review of cross-lan- Experience: Issues in Cross-Language guage studies in speech perception pro- Research viding a clear conceptual framework of York Press, Timonium, 1995 the topic. Strange presents a selective his- 492 pp.; $ 59 tory of research that highlights the main ISBN 0–912752–36–X theoretical themes and methodological paradigms. It begins with a brief descrip- How is speech perception shaped by tion of the basic phenomena that are the experience with our native language and starting points for the investigation: the by exposure to subsequent languages? constancy problem and the question of This is a central research question in units of analysis in speech perception. language perception, which emphasizes Next, the author presents the principal the importance of crosslinguistic studies. theories, methods, findings and limita- Speech Perception and Linguistic Experi- tions in early cross-language research, ence: Issues in Cross-Language Research focused on categorical perception as the contains the contributions to a Workshop dominant paradigm in the study of adult in Cross-Language Perception held at the and infant perception in the 1960s and University of South Florida, Tampa, Fla., 1970s. Finally, Strange reviews the most USA, in May 1992. important findings and conclusions in This text may be said to represent recent cross-language research (1980s and the first compilation strictly focused on early 1990s), which yielded a large theoretical and methodological issues of amount of new information from a wider cross-language perception research.
    [Show full text]
  • The Physics of Sound 1
    The Physics of Sound 1 The Physics of Sound Sound lies at the very center of speech communication. A sound wave is both the end product of the speech production mechanism and the primary source of raw material used by the listener to recover the speaker's message. Because of the central role played by sound in speech communication, it is important to have a good understanding of how sound is produced, modified, and measured. The purpose of this chapter will be to review some basic principles underlying the physics of sound, with a particular focus on two ideas that play an especially important role in both speech and hearing: the concept of the spectrum and acoustic filtering. The speech production mechanism is a kind of assembly line that operates by generating some relatively simple sounds consisting of various combinations of buzzes, hisses, and pops, and then filtering those sounds by making a number of fine adjustments to the tongue, lips, jaw, soft palate, and other articulators. We will also see that a crucial step at the receiving end occurs when the ear breaks this complex sound into its individual frequency components in much the same way that a prism breaks white light into components of different optical frequencies. Before getting into these ideas it is first necessary to cover the basic principles of vibration and sound propagation. Sound and Vibration A sound wave is an air pressure disturbance that results from vibration. The vibration can come from a tuning fork, a guitar string, the column of air in an organ pipe, the head (or rim) of a snare drum, steam escaping from a radiator, the reed on a clarinet, the diaphragm of a loudspeaker, the vocal cords, or virtually anything that vibrates in a frequency range that is audible to a listener (roughly 20 to 20,000 cycles per second for humans).
    [Show full text]
  • Categorical Speech Processing in Broca's Area
    3942 • The Journal of Neuroscience, March 14, 2012 • 32(11):3942–3948 Behavioral/Systems/Cognitive Categorical Speech Processing in Broca’s Area: An fMRI Study Using Multivariate Pattern-Based Analysis Yune-Sang Lee,1 Peter Turkeltaub,2 Richard Granger,1 and Rajeev D. S. Raizada3 1Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire 03755, 2Neurology Department, Georgetown University, Washington, DC, 20057 and 3Neukom Institute, Dartmouth College, Hanover, New Hampshire 03755 Although much effort has been directed toward understanding the neural basis of speech processing, the neural processes involved in the categorical perception of speech have been relatively less studied, and many questions remain open. In this functional magnetic reso- nance imaging (fMRI) study, we probed the cortical regions mediating categorical speech perception using an advanced brain-mapping technique, whole-brain multivariate pattern-based analysis (MVPA). Normal healthy human subjects (native English speakers) were scanned while they listened to 10 consonant–vowel syllables along the /ba/–/da/ continuum. Outside of the scanner, individuals’ own category boundaries were measured to divide the fMRI data into /ba/ and /da/ conditions per subject. The whole-brain MVPA revealed that Broca’s area and the left pre-supplementary motor area evoked distinct neural activity patterns between the two perceptual catego- ries (/ba/ vs /da/). Broca’s area was also found when the same analysis was applied to another dataset (Raizada and Poldrack, 2007), which previously yielded the supramarginal gyrus using a univariate adaptation–fMRI paradigm. The consistent MVPA findings from two independent datasets strongly indicate that Broca’s area participates in categorical speech perception, with a possible role of translating speech signals into articulatory codes.
    [Show full text]
  • Focal Versus Distributed Temporal Cortex Activity for Speech Sound Category Assignment
    Focal versus distributed temporal cortex activity for PNAS PLUS speech sound category assignment Sophie Boutona,b,c,1, Valérian Chambona,d, Rémi Tyranda, Adrian G. Guggisberge, Margitta Seecke, Sami Karkarf, Dimitri van de Villeg,h, and Anne-Lise Girauda aDepartment of Fundamental Neuroscience, Biotech Campus, University of Geneva,1202 Geneva, Switzerland; bCentre de Recherche de l′Institut du Cerveau et de la Moelle Epinière, 75013 Paris, France; cCentre de Neuro-imagerie de Recherche, 75013 Paris, France; dInstitut Jean Nicod, CNRS UMR 8129, Institut d’Étude de la Cognition, École Normale Supérieure, Paris Science et Lettres Research University, 75005 Paris, France; eDepartment of Clinical Neuroscience, University of Geneva – Geneva University Hospitals, 1205 Geneva, Switzerland; fLaboratoire de Tribologie et Dynamique des Systèmes, École Centrale de Lyon, 69134 Ecully, France; gCenter for Neuroprosthetics, Biotech Campus, Swiss Federal Institute of Technology, 1202 Geneva, Switzerland; and hDepartment of Radiology and Medical Informatics, Biotech Campus, University of Geneva, 1202 Geneva, Switzerland Edited by Nancy Kopell, Boston University, Boston, MA, and approved December 29, 2017 (received for review August 29, 2017) Percepts and words can be decoded from distributed neural activity follow from these operations, reflect associative processes, or measures. However, the existence of widespread representations arise from processing redundancy. This concern is relevant at any might conflict with the more classical notions of hierarchical
    [Show full text]
  • Investigating the Neural Correlates of Voice Versus Speech-Sound Directed Information in Pre-School Children
    Investigating the Neural Correlates of Voice versus Speech-Sound Directed Information in Pre-School Children The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Raschle, Nora Maria, Sara Ashley Smith, Jennifer Zuk, Maria Regina Dauvermann, Michael Joseph Figuccio, and Nadine Gaab. 2014. “Investigating the Neural Correlates of Voice versus Speech-Sound Directed Information in Pre-School Children.” PLoS ONE 9 (12): e115549. doi:10.1371/journal.pone.0115549. http:// dx.doi.org/10.1371/journal.pone.0115549. Published Version doi:10.1371/journal.pone.0115549 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:13581019 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA RESEARCH ARTICLE Investigating the Neural Correlates of Voice versus Speech-Sound Directed Information in Pre-School Children Nora Maria Raschle1,2,3*, Sara Ashley Smith1, Jennifer Zuk1,2, Maria Regina Dauvermann1,2, Michael Joseph Figuccio1, Nadine Gaab1,2,4 1. Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Developmental Medicine, Boston Children’s Hospital, Boston, Massachusetts, United States of America, 2. Harvard Medical School, Boston, Massachusetts, United States of America, 3. Psychiatric University Clinics Basel, Department of Child and Adolescent Psychiatry, Basel, Switzerland, 4. Harvard Graduate School of Education, Cambridge, Massachusetts, United States of America *[email protected] OPEN ACCESS Citation: Raschle NM, Smith SA, Zuk J, Dauvermann MR, Figuccio MJ, et al.
    [Show full text]
  • Articulatory Feature-Based Pronunciation Modeling
    Articulatory Feature-Based Pronunciation Modeling Karen Livescu1a, Preethi Jyothib, Eric Fosler-Lussierc aTTI-Chicago, Chicago, IL, USA bBeckman Institute, UIUC, Champaign, IL, USA cDepartment of Computer Science and Engineering, OSU, Columbus, OH, USA Abstract Spoken language, especially conversational speech, is characterized by great variability in word pronunciation, including many variants that differ grossly from dictionary prototypes. This is one factor in the poor performance of automatic speech recognizers on conversational speech, and it has been very difficult to mitigate in traditional phone- based approaches to speech recognition. An alternative approach, which has been studied by ourselves and others, is one based on sub-phonetic features rather than phones. In such an approach, a word’s pronunciation is represented as multiple streams of phonological features rather than a single stream of phones. Features may correspond to the positions of the speech articulators, such as the lips and tongue, or may be more abstract categories such as manner and place. This article reviews our work on a particular type of articulatory feature-based pronunciation model. The model allows for asynchrony between features, as well as per-feature substitutions, making it more natural to account for many pronunciation changes that are difficult to handle with phone-based models. Such models can be efficiently represented as dynamic Bayesian networks. The feature-based models improve significantly over phone-based coun- terparts in terms of frame perplexity and lexical access accuracy. The remainder of the article discusses related work and future directions. Keywords: speech recognition, articulatory features, pronunciation modeling, dynamic Bayesian networks 1. Introduction Human speech is characterized by enormous variability in pronunciation.
    [Show full text]
  • Science Workshop with Sliding Vocal-Tract Model
    Science Workshop with Sliding Vocal-Tract Model Takayuki Arai Department of Information and Communication Sciences Sophia University, Tokyo, Japan [email protected] many attractive scientific subjects are around us. Speech science ABSTRACT is one such subject. In our daily life, we communicate verbally, In recent years, we have developed physical models of the vocal so speech science should be a familiar subject, even to children. tract to promote education in the speech sciences for all ages of Our goal is to develop educational tools and programs students. Beginning with our initial models based on Chiba and because visualizing physical phenomena is intuitive and Kajiyama’s measurements, we have gone on to present many teaching with physical models is very effective. And ultimately, other models to the public. Through science fairs which attract we are hoping that introducing topics in speech science by using all ages, including elementary through college level students, we an intuitive approach with physical models will increase have sought to increase awareness of the importance of the children’s interest in science. We are also hoping we can speech sciences in the public mind. In this paper we described improve their logical thinking skills, teach the importance of two science workshops we organized at the National Science speech and language, and raise their consideration for people Museum in 2006 and 2007 in Japan. with speech and language disorders. Index Terms: speech production, vocal-tract model, science We have developed physical models of the human vocal workshop, sliding three-tube model, education in acoustics tract. One of the early models [1], shown in Fig.
    [Show full text]
  • Event-Related Functional MRI Investigation of Vocal Pitch Variation☆
    NeuroImage 44 (2009) 175–181 Contents lists available at ScienceDirect NeuroImage journal homepage: www.elsevier.com/locate/ynimg Event-related functional MRI investigation of vocal pitch variation☆ Kyung K. Peck a,b,⁎, Jessica F. Galgano c,d, Ryan C. Branski d, Dmitry Bogomolny d, Margaret Ho d, Andrei I. Holodny a, Dennis H. Kraus d a Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA b Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA c Department of Speech-Language Pathology, Teacher's College, Columbia University, New York, NY, USA d Department of Head and Neck Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA article info abstract Article history: Voice production involves precise, coordinated movements of the intrinsic and extrinsic laryngeal Received 27 May 2008 musculature. A component of normal voice production is the modification of pitch. The underlying neural Revised 15 August 2008 networks associated with these complex processes remains poorly characterized. However, several Accepted 22 August 2008 investigators are currently utilizing neuroimaging techniques to more clearly delineate these networks Available online 10 September 2008 associated with phonation. The current study sought to identify the central cortical mechanism(s) associated with pitch variation during voice production using event-related functional MRI (fMRI). A single-trial design was employed consisting of three voice production tasks (low, comfortable, and high pitch) to contrast brain activity during the generation of varying frequencies. For whole brain analysis, volumes of activation within regions activated during each task were measured. Bilateral activations were shown in the cerebellum, superior temporal gyrus, insula, precentral gyrus, postcentral gyrus, inferior parietal lobe, and post-cingulate gyrus.
    [Show full text]
  • Running Head: SPEECH and EXERCISE
    ABSTRACT EXAMINATION OF SPEECH AND RESPIRATORY PARAMETERS DURING MODERATE AND HIGH INTENSITY WORK by Jenny Christine Hipp Speaking while performing physical work tasks is known to decrease ventilation, which may in turn, impair speech fluency. The purpose of this study was to determine how speech fluency is affected during a simultaneous speech and work task performed at two work intensity levels. Twelve healthy participants performed steady-state work tasks at either 50% or 75% of VO2 max (maximal O2 uptake) for a total of six minutes after completing a rest-to-work transition period. Initially the participants did not speak, but when they returned for further testing, a similar task was completed with the addition of speaking. Results demonstrated significant differences in dyspnea ratings, number of words per phrase, and number of inappropriate pauses between the two intensity levels. The speaking condition influenced all variables except heart rate. The higher intensity task was more challenging for the participants and had the greatest impact on speech fluency. EXAMINATION OF SPEECH AND RESPIRATORY PARAMETERS DURING MODERATE AND HIGH INTENSITY WORK A Thesis Submitted to the Faculty of Miami University in partial fulfillment of the requirements for the degree of Masters of Arts Department of Speech Pathology and Audiology by Jenny Christine Hipp Miami University Oxford, OH 2005 Advisor_____________________________ Susan Baker, Ph.D. Reader______________________________ Helaine Alessio, Ph.D. Reader______________________________ Kathleen Hutchinson, Ph.D. TABLE OF CONTENTS CHAPTER I: Introduction……………………………………………………………….. 1 Control of Involuntary Respiration……………………………………………… 1 Voluntary Control of Respiration………………………………………………... 2 Introduction to Respiration and Speaking……………………………………….. 2 Introduction to Respiration and Working………………………………………... 3 Respiration, Speech, and Work………………………………………………….
    [Show full text]