Harvard-MIT Division of Health Sciences and Technology HST.722J: Brain Mechanisms for Hearing and Speech Course Instructor: Joseph S. Perkell Motor Control of Speech: Control Variables and Mechanisms HST 722, Brain Mechanisms for Hearing and Speech Joseph S. Perkell MIT 111/2/05Outline • Introduction • Measuring speech production • What are the “controlled variables” for segmental (phonemic) speech movements? • Segmental motor programming goals • Producing speech sounds in sequences • Experiments on feedback control • Summary 2112/05Outline • Introduction – Utterance planning – General physiological/neurophysiological features – The controlled systems – Example of movements of vocal-tract articulators • Measuring speech production • What are the “controlled variables” for segmental speech movements? • Segmental motor programming goals • Producing speech sounds in sequences • Experiments on feedback control • Summary 3112/05Utterance Planning • Objective: generate an intelligible message while providing for �“economy of effort” – stages: �– Form the message (e.g. Feel hungry; smell pizza; together with a friend). – Select and sequence lexical items (words). “Do you want a pizza?” – Assign a syntactically-governed prosodic structure. – Determine “postural” parameters of overall rate, loudness and degree of reduction (and settings that convey emotional state, etc.) • Extreme reduction: “Dja wanna pizza?” – Determine temporal patterns: Sound segment durations depend on: • Phoneme length • Overall rate • Intrinsic characteristics of sounds • Position and number of syllables in word • Result: an ordered sequence of goals for the production mechanism 4112/05Serial Ordering• Evidence reflecting serial ordering in utterance planning: speech errors – Examples from Shattuck-Hufnagel (1979) • Substitution Anymay (Anyway) • Exchange emeny (enemy) • Shift bad highvway dri_ing (highway driving) • Addition the plublicity would be (publicity) • Omission sonata _umber ten (number) • ? dignal sigital processing –See Averbeck et al. on neurophysiologial evidence concerning serial ordering 5112/05General Physiological/Neurophysiological Features • Muscles are under voluntary control • Structures contain feedback receptors that supply sensory information to the CNS: – Surfaces: touch/pressure – Muscles: • length and length changes: spindles • Tension: tendon organs – Joints (TMJ): joint angle • Reflex mechanisms: – Stretch – Laryngeal (coughing) – Startle • Motor programs (low-level, “hard wired” neural pattern generators) – Breathing – Swallowing – Chewing – Sucking Pharynx Larynx Epiglottis Lips Arytenoid cartilage Esophagus Lungs Soft palate Vocal cords Nasal cavity Tongue Hyoid Teeth Trachea Diaphragm Adam's apple Thyroid cartilage Cricoid cartilage • Low-level circuitry could be employed in Figure by MIT OCW. speech motor control. The picture is complex, and a comprehensive account hasn’t emerged. 112/05 6The controlled systems • The respiratory system – most massive (slowly-moving structures) – Provides energy for sound production • Fluctuations to help signal emphasis • Relatively constant level of subglottal pressure – Different patterns of respiration: breathing, reading aloud, spontaneous, counting – Different muscles are active at different phases of the respiratory cycle – a complex, low-level motor program • Larynx – Smallest structures, most rapidly contracting muscles – Voicing, turned on and off segment-by-segment – F0, breathiness – suprasegmental regulation • Vocal tract – Intermediate-sized, slowly moving structures: tongue, lips, velum, mandible – Many muscles do not insert on hard structures – Can produce sounds at rates up to 15/sec – To do so, the movements are coarticulated Figures removed due to copyright reasons. 7112/05 Please see: Conrad, B., and P. Schonle. "Speech and respiration." Arch Psychiatr Nervenkr 226, no. 4 (1979): 251-68.Velum LipsTongue blade Tongue body Focus of lecture is on movements of vocal-tract articulators• Consider the movements of each of these structures • Approximate number of muscle pairs that move the – Tongue: 9 – Velum: 3 – Lips: 12Mandible – Mandible: 7 – Hyoid bone: 10 Hyoid bone – Larynx: 8 – Pharynx: 4 Larynx • Not including the respiratory system • Observations: • A large number of degrees of freedom • A very complicated control problem 8112/05Outline• Introduction • Measuring speech production – Acoustics – Articulatory movement – Area functions • What are the “controlled variables” for segmental speech movements? • Segmental motor programming goals • Producing speech sounds in sequences • Experiments on feedback control • Summary 9112/05•� Acoustics – important for perception Measuring Speech Production – Spectral, temporal and amplitude measures •� Vowels, liquids and glides: – Time varying patterns of formant frequencies •� Consonants: – Noise bursts � Figure removed due to copyright reasons. – Silent intervals – Aspiration and frication noises – Rapid formant transitions “The yacht was a heavy one” From: Perkell, Joseph S. Physiology of Speech Production: Results and Implications of a Quantitative Cineradiographic Study. Research Monograph No. 53. Cambridge, MA: •� Movements MIT Press. 1969(c). Used with permission. – From x-ray tracings – With an Electro-MagneticMidsagittal Articulometer(EMMA) System •� Points on the tongue, lips, jaw, (velum) �Reprinted with permission from: Perkell, J., M. Cohen, M. Svirsky, M. Matthies, I. Garabieta, and M. Jackson. "Electro-magnetic midsagittal articulometer (EMMA) systems • Other parameters: air pressures �for transducing speech articulatory movements. J Acoust Soc Am 92 (1992): and flows, muscle activity …�3078-3096. Copyright 1992, Acoustical Society America. 112/05 10 Please see: Steven, K. Acoustic Phonetics. Cambridge, MA: MIT Press, 1998, p. 248. ISBN: 026219404X.EMMA Data Collection• Transducer coils are placed on subject’s articulators • Subject reads text from an LCD screen • Movement and audio signals are digitized and displayed in real time • Signals are processed and data are extracted and analyzed 11112/05112/0512Analysis of EMMA data• Algorithmic data extraction
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