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Of the Linguistic Society of Ameri
1856c ARTHUR S. ABRAMSON Arthur S. Abramson, former Secretary, Vice President, and President (1983) of the Linguistic Society of America, died on December 15, 2017, at the age of ninety-two.1 He was a central figure in the linguistic study of tone, voicing, voice quality, and duration, primarily in their phonetic realization. His seminal work with Leigh Lisker (Lisker & Abramson 1964) introduced the metric VOICE ONSET TIME (VOT), which has become per- haps the most widely used measure in phonetics. He contributed to the field in numerous other ways; in addition to his work for the LSA, he became the first chair of the Linguis- tics Department of the University of Connecticut, served as editor of Language and Speech, and was a long-term researcher and board member of Haskins Laboratories. LIFE. Arthur was born January 26, 1925, in Jersey City, New Jersey. He learned Bib- lical Hebrew in his childhood, and then followed up with post-Biblical Hebrew later on. Yiddish was also part of his background. His parents were born in the US, but his grandparents were not, and they primarily spoke Yiddish. He learned some from his mother, and it came in handy when he served in the US Army in Europe during World War II. (Many years later, he taught it at the University of Connecticut in the Center for Judaic Studies, which he helped establish.) He became fluent in French, starting from classes in high school, where he was lucky enough to have a native speaker as a teacher. (The teacher was Belgian, and Arthur was sometimes said, by French colleagues, to have a Belgian accent.) Arthur had an early introduction to synthetic speech when he at- tended the New York World’s Fair in 1939. -
La Voz Humana
UNIVERSIDAD DE CHILE FACULTAD DE ARTES MAGISTER EN ARTES MEDIALES SHOUT! Tesis para optar al Grado de Magíster en Artes Medialess ALUMNO: Christian Oyarzún Roa PROFESOR GUÍA: Néstor Olhagaray Llanos Santiago, Chile 2012 A los que ya no tienen voz, a los viejos, a los antiguos, a aquellos que el silencio se lleva en la noche. ii AGRADECIMIENTOS Antes que nada quiero agradecer a Néstor Olhagaray, por el tesón en haberse mantenido como profesor guía de este proyecto y por la confianza manifestada más allá de mis infinitos loops y procastinación. También quisiera manifestar mis agradecimientos a Álvaro Sylleros quién, como profesor del Diplomado en Lutería Electrónica en la PUC, estimuló y ayudó a dar forma a parte sustancial de lo aquí expuesto. A Valentina Montero por la ayuda, referencia y asistencia curatorial permanente, A Pablo Retamal, Pía Sommer, Mónica Bate, Marco Aviléz, Francisco Flores, Pablo Castillo, Willy MC, Álvaro Ceppi, Valentina Serrati, Yto Aranda, Leonardo Beltrán, Daniel Tirado y a todos aquellos que olvido y que participaron como informantes clave, usuarios de prueba ó simplemente apoyando entusiastamente el proyecto. Finalmente, quiero agradecer a Claudia González, quien ha sido una figura clave dentro de todo este proceso. Gracias Clau por tu sentido crítico, por tu presencia inspiradora y la ejemplar dedicación y amor por lo que haces. iii Tabla de Contenidos RESÚMEN v INTRODUCCIÓN 1 A Hard Place 1 Descripción 4 Objetivos 6 LA VOZ HUMANA 7 La voz y el habla 7 Balbuceos, risas y gritos 11 Yo no canto por cantar 13 -
Status Report on Speech Research
DOCumENT RESI.TME ED 278 066 CS 505 474 AUTHOR O'Brien, Nancy, Ed. TITLE Status Report on Speech Research: AReport on the Status and Progress of Studieson the Nature of Speech, Instrumentation for Its Investigation,and Practical Applications, April 1-September30, 1986. INSTITUTION Haskins Labs., New Haven, Conn. SPONS AGENCY National Institutes of Health (DHHS),Bethesda, Md.; National Science Foundation, Washington,D.C.; Office of Naval_Research, Washington,D.C. REPORT NO SR-86/87(1986) PUB DATE 86 CONTRACT NICHHD-N01-HD-5-2910; ONR-N00014-83-K-0083 GRANT NICHHD-HD-01994; NIH-BRS-RR-05596;NINCDS-NS-13617; NINCDS-N5-13870; NINCDS-NS-18010;NSF-DNS-8111470; NSF-BNS-8520709 NOTE 319p.; For the previous report,see ED 274 022. AVAILABLE FROMU.S. Department of Commerce, NationalTechnical Information Service, 5285 Port RoyalRd., Springfield, VA 22151. PUB TYPE Reports - ReseimrtM/Technical (143) information Analyses (070)-- Collected Works - General (020) EDRS PRICE MF01/PC13 Plus Postage_. DESCRIPTORS *Communication Research*Morphology (Languages); *Research Methodology; Research Utilization; *Speech Communication ABSTRACT Focusing on the status,progress, instrumentation, and applications of_studieson the nature of speech, this report contains the following research_studies:"The Role of Psychophysics in Understanding Speech Perception" (B.H. Repp); "Specialized Perceiving Systems for Speech and OtherBiologically Significant Sounds" (I. G. Mattingly; A. M. Liberman);"'Voicing' in EnglishA Catalog of Acoustic Features Signaling /b/_versus/p/ in Trochees (L. Lisker); "Categorical Tendenciesin Imitating Self-Produced Isolated Vowels" (B. H. Repp; D. R. Williams);"An Acoustic Analysis of V-to-C and V-to-V: Coarticulatory Effectsin Catalan and Spanish VCV Sequences" (D. -
Aac 2, 3, 4, 5, 6, 50, 51, 52, 53, 55, 56, 57, 58, 59, 60, 61, 62
315 Index A augmentative and alternative communication (AAC) 130, 145, 148 AAC 2, 3, 4, 5, 6, 50, 51, 52, 53, 55, 56, 57, Augmentative and Alternative Communication 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, (AAC) 50 69, 130, 131, 138, 140, 141, 142, 143, augmented speech 116, 126 144, 145, 147, 148, 149, 150, 153, 156, Augmented Speech Communication 117 158, 159, 160, 161, 162, 163, 164, 165, Augmented speech communication (ASC) 116 172, 173, 174, 175, 192, 194, 198, 205, automatic categorization 220 206, 207, 208, 213, 214, 215, 216, 257, automatic speech recognition 100 258, 259, 260, 263, 265 Automatic Speech Recognition (ASR) 189 able-bodied people 220 accessibility 12, 14, 15, 21 B acoustic energy 31 adaptive differential pulse code modulation background noise 56, 67, 130, 132, 134, 135, (ADPCM) 32 136, 137, 141, 142, 144 AIBO 17 BCI 17 aided communication techniques 205 bit rate 31, 32, 33, 41, 45, 47 aided communicator 234, 235, 241, 243, 245, bits per second (bps) 31 248, 250, 252 Blissymbols 235, 238, 239, 240, 241, 242, 243, aided language development 235 244, 246, 247, 250, 256 allophones 34, 35 brain-computer interfaces (BCI) 17 alternate reader 17 Brain Computer Interfaces (BCI’s) 6 alternative and augmentative communication brain-machine interface (BMI) 17 (AAC) 2, 93 C alternative communication 1 amyotrophic lateral sclerosis (ALS) 1 CALL 189, 190, 191, 192, 193, 196, 198, 199, analog-to-digital converter 30, 31 201, 202, 203 anti-aliasing (low-pass) filters 3 1 CASLT 188, 189, 190, 191, 193, 198, 199 aphasia 148, 149, -
WIKI on ACCESSIBILITY Completion Report March 2010
WIKI ON ACCESSIBILITY Completion report March 2010 By Nirmita Narasimhan Programme Manager Centre for Internet and Society Project Title: Wiki on “Accessibility, Disability and the Internet in India” Page | 1 REPORT Accessibility wiki: accessibility.cis-india.org The wiki project was envisaged and funded by the National Internet Exchange of India (www.nixi.in) and has been executed by the Centre for Internet and Society (www.cis-india.org), Bangalore. Project Start date: May 2009 End date: February 2010. Background India has a large percentage of disabled persons in its population— estimated to be over seven per cent as per the Census of 2001. Even this figure is believed to be a gross under representation of the total number of disabled persons residing in this large and diverse country. Taken in figures, this amounts to roughly 70-100 million persons with disabilities in the territory of India. Out of this number, a mere two per cent residing in urban areas have access to information and assistive technologies which enable them to function in society and enhance their performance. There are several reasons for this, one of them being that there is a deplorable lack of awareness which exists on the kinds of disabilities and about ways in which one can provide information and services to disabled persons. Parents, teachers, government authorities and society at large are all equally unaware about the options which exist in technology today to enable persons with disabilities to carry on independent and productive lives. Barring a few exceptions, India is still trapped in an era where a white cane and a Braille slate symbolises the future for blind people, while the world has progressed to newer forms of enabling technology such as screen readers, daisy players, the Kindle and so on. -
Chapter 10 Speech Synthesis Ch T 11 a T Ti S H R Iti Chapter 11 Automatic
Chapter 10 Speech Synthesis Chapt er 11 Aut omati c Speech Recogniti on 1 An Enggpineer’s Perspective Speech production Speech analysis ShSpeech Speech Speech quality coding recognition assessment Speech Speech Speaker synthesis enhancement recognition 2 3 4 History Long before modern electronic signal processing was invented, speech researchers tried to build machines to create human speech. Early examples of 'speaking heads' were made by Gerbert of Aurillac (d. 1003), Albertus Magnus (1198-1280), and Roger Bacon (1214-1294). In 1779, the Danish scientist Christian Kratzenstein, working at the time at the Russian Academy of Sciences, built models of the human vocal tract that could produce the five long vowel sounds (a, e, i, o and u). 5 Kratzenstein's resonators 6 Engineering the vocal tract: Riesz 1937 7 Homer Dudley 1939 VODER Synthesizing speech by electrical means 1939 World’s Fair •Manually controlled through complex keyboard •Operator training was a problem 8 Cooper’s Pattern Playback Haskins Labs for investigating speech perception Works like an inverse of a spectrograph Light from a lamp goes through a rotating disk then througgph spectrog ram into photovoltaic cells Thus amount of light that gets transmitted at eachfh frequency b and correspond s to amount of acoustic energy at that band 9 Cooper’s Pattern Playback 10 Modern TTS systems 1960’s first full TTS: Umeda et al (1968) 1970’s Joe Olive 1977 concatenation of linear-prediction diphones Speak and Spell 1980’s 1979 MIT MITalk (Allen, Hunnicut, Klatt) 1990’s-present Diphone synthesis Unit selection synthesis 11 Types of Modern Synthesis Articulatory Synthesis: Model movements of articulators and acoustics o f voca l trac t Formant Synthesis: Start with acoustics,,/ create rules/filters to create each formant Concatenative Synthesis: Use databases of stored speech to assemble new utterances. -
Memory Interference As a Determinant of Language Comprehension Julie A
Language and Linguistics Compass 6/4 (2012): 193–211, 10.1002/lnc3.330 Memory Interference as a Determinant of Language Comprehension Julie A. Van Dyke* and Clinton L. Johns Haskins Laboratories Abstract The parameters of the human memory system constrain the operation of language comprehension processes. In the memory literature, both decay and interference have been proposed as causes of forgetting; however, while there is a long history of research establishing the nature of interference effects in memory, the effects of decay are much more poorly supported. Nevertheless, research investigating the limitations of the human sentence processing mechanism typically focus on decay-based explanations, emphasizing the role of capacity, while the role of interference has received comparatively little attention. This paper reviews both accounts of difficulty in language comprehension by drawing direct connections to research in the memory domain. Capacity-based accounts are found to be untenable, diverging substantially from what is known about the opera- tion of the human memory system. In contrast, recent research investigating comprehension difficulty using a retrieval-interference paradigm is shown to be wholly consistent with both behavioral and neuropsychological memory phenomena. The implications of adopting a retrieval- interference approach to investigating individual variation in language comprehension are discussed. 1. Introduction One of the most fascinating properties of natural language is the fact that related pieces of information need not be adjacent. For instance, the subject of a sentence (athlete) may be separated from its verb (ran) by just a few words (1), or by many words, phrases, or even clauses (2–4): (1) The athlete in the training program ran every day. -
The Psychology of Language, Reading & Writing
The Psychology of Language, Reading & Writing Books & Journals CONTENTS Psychology of Reading, 2nd Ed., Rayner et al. .................................................................. 4 Explaining Individual Differences in Reading, Brady et al., Eds. .......................................5 Contents Reading and Dyslexia in Different Orthographies, Brunswick et al., Eds. .........................6 How Children Learn to Read, Pugh & McCardle, Eds. ...................................................... 7 Writing, Grigorenko et al., Eds. ........................................................................................ 8 Translation of Thought to Written Text While Composing, Fayol et al., Eds. ...................9 Past, Present, and Future Contributions of Cognitive Writing Research to Cognitive Psychology, Berninger (Ed.) .............................................................................. 10 Talking Heads, Denes ........................................................................................................ 11 The Tip of the Tongue State, Brown ................................................................................ 12 Language and Bilingual Cognition, Cook & Bassetti, Eds. ................................................ 13 Language and Cognition in Bilinguals and Multilinguals, de Groot ..................................14 Crosslinguistic Approaches to the Psychology of Language, Guo et al., Eds. ...................15 Perspectives on Framing, Keren, Ed. ............................................................................... -
Arthur S. Abramson
LAS0010.1177/0023830918780146Language and SpeechWhalen and Koenig 780146research-article2018 1856 Language Obituary and Speech Language and Speech 2018, Vol. 61(2) 334 –336 Arthur S. Abramson © The Author(s) 2018 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav https://doi.org/10.1177/0023830918780146DOI: 10.1177/0023830918780146 journals.sagepub.com/home/las D. H. Whalen City University of New York, Haskins Laboratories, Yale University, USA Laura L. Koenig Adelphi University, Haskins Laboratories, USA Arthur S. Abramson, editor of Language and Speech from 1975 to 1987, died on 15 December 2017, at the age of 92. He was a central figure in the study of the phonetic realizations of linguistic distinctions of tone, voicing, voice quality, and duration. His seminal work with Leigh Lisker on the metric, voice onset time (VOT) (Lisker & Abramson, 1964), has become perhaps the most extensively used measure in phonetics. He contributed to his profession in many ways beyond his research, serving as the first chair of the Linguistics Department of the University of Connecticut, president (and other roles) of the Linguistic Society of America, and a researcher and Board mem- ber of Haskins Laboratories. In the early 1950s, while still a graduate student in linguistics at Columbia University, New York, Arthur mentioned to colleagues and people at the Department of State that he was very inter- ested in Southeast Asian languages and culture. He was recommended to apply for a Fulbright teaching grant, which he received. Arthur spent 1953–1955 teaching English in Thailand, begin- ning in the south (Songkhla), and later moving to Bangkok. This experience started a decades-long relationship with the language and people of Thailand. -
Speech Generation: from Concept and from Text
Speech Generation From Concept and from Text Martin Jansche CS 6998 2004-02-11 Components of spoken output systems Front end: From input to control parameters. • From naturally occurring text; or • From constrained mark-up language; or • From semantic/conceptual representations. Back end: From control parameters to waveform. • Articulatory synthesis; or • Acoustic synthesis: – Based predominantly on speech samples; or – Using mostly synthetic sources. 2004-02-11 1 Who said anything about computers? Wolfgang von Kempelen, Mechanismus der menschlichen Sprache nebst Beschreibung einer sprechenden Maschine, 1791. Charles Wheatstone’s reconstruction of von Kempelen’s machine 2004-02-11 2 Joseph Faber’s Euphonia, 1846 2004-02-11 3 Modern articulatory synthesis • Output produced by an articulatory synthesizer from Dennis Klatt’s review article (JASA 1987) • Praat demo • Overview at Haskins Laboratories (Yale) 2004-02-11 4 The Voder ... Developed by Homer Dudley at Bell Telephone Laboratories, 1939 2004-02-11 5 ... an acoustic synthesizer Architectural blueprint for the Voder Output produced by the Voder 2004-02-11 6 The Pattern Playback Developed by Franklin Cooper at Haskins Laboratories, 1951 No human operator required. Machine plays back previously drawn spectrogram (spectrograph invented a few years earlier). 2004-02-11 7 Can you understand what it says? Output produced by the Pattern Playback. 2004-02-11 8 Can you understand what it says? Output produced by the Pattern Playback. These days a chicken leg is a rare dish. It’s easy to tell the depth of a well. Four hours of steady work faced us. 2004-02-11 9 Synthesis-by-rule • Realization that spectrograph and Pattern Playback are really only recording and playback devices. -
References and Appendices
REFERENCES Acalin, T. A. (1995). A comparison of Reading Recovery to Project Read. Unpublished master’s thesis, California State University, Fullerton. Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press. Allington, R. L. (2001). What really matters for struggling readers: Designing research-based programs. New York: Longman. Allington, R. L., & Cunningham, P. M. (2002). Schools that work: Where all children read and write. Boston, MA: Allyn & Bacon. Allington, R. L., & Walmsley, S. A. (1995). No quick fix: Where do we go from here? In R. L. Allington & S. A. Walmsley, (Eds.), No quick fix: Rethinking literacy programs in America’s ele- mentary schools (pp. 253–264). New York: Teachers College Press. Askew, B. J., Kaye, E., Frasier, D. F., Mobasher, M., Anderson, N., & Rodríguez, Y. (2002). Making a case for prevention in education. Literacy Teaching and Learning: An International Journal of Early Reading and Writing, 6(2), 43–73. Assad, S., & Condon, M. A. (1996, Winter). Demonstrating the cost-effectiveness of Reading Recovery: Because it makes a difference. Network News, 10–14. Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall. Barnett, S. W. (1993). Economic evaluation of home visiting programs. The Future of Children, 3, 93–112. Bloom, B. (1984). The 2-sigma problem: The search for methods of group instruction as effective one-to-one tutoring. Educational Researcher, 13, 4–16. Brown, W., Denton, E., Kelly, P., & Neal, J. (1999). Reading Recovery effectiveness: A five-year suc- cess story in San Luis Coastal Unified School District. ERS Spectrum: Journal of School Research and Information, 17(1), 3–12. -
Gnuspeech Tract Manual 0.9
Gnuspeech TRAcT Manual 0.9 TRAcT: the Gnuspeech Tube Resonance Access Tool: a means of investigating and understanding the basic Gnuspeech vocal tract model David R. Hill, University of Calgary TRAcT and the \tube" model to which it allows access was originally known as \Synthesizer" and developed by Leonard Manzara on the NeXT computer. The name has been changed because \Synthesiser" might be taken to imply it synthesises speech, which it doesn't. It is a \low-level" sound synthesiser that models the human vocal tract, requiring the \high-level" synthesiser control inherent in Gnuspeech/Monet to speak. TRAcT provides direct interactive access to the human vocal tract model parameters and shapes as a means of exploring its sound generation capabilities, as needed for speech database creation. i (GnuSpeech TRAcT Manual Version 0.9) David R. Hill, PEng, FBCS ([email protected] or drh@firethorne.com) © 2004, 2015 David R. Hill. All rights reserved. This document is publicly available under the terms of a Free Software Foundation \Free Doc- umentation Licence" See see http://www.gnu.org/copyleft/fdl.html for the licence terms. This page and the acknowledgements section are the invariant sections. ii SUMMARY The \Tube Resonance Model" (TRM, or \tube", or \waveguide", or transmission-line) forms the acoustic basis of the Gnupeech articulatory text-to-speech system and provides a linguistics research tool. It emulates the human vocal apparatus and allows \postures" to be imposed on vocal tract model, and energy to be injected representing voicing, whispering, sibilant noises and \breathy" noise. The \Distinctive Region Model" (DRM) control system that allows simple specification of the postures, and accessed by TRAcT 1is based on research by CGM Fant and his colleagues at the Stockholm Royal Institute of Technology Speech Technology Laboratory (Fant & Pauli 1974), by Ren´eCarr´eand his colleagues at T´el´ecomParis (Carr´e,Chennoukh & Mrayati 1992), and further developed by our original research team at Trillium Sound Research and the U of Calgary).