Articulation and Intelligibility: (Synthesis Lectures on Speech and Audio Processing)

Immediately following the Second World War, between 1947 and 1955, several classic papers quantified the fundamentals of human speech information processing and recognition. In 1947 French and Steinberg published their classic study on the articulation index. In 1948 Claude Shannon published his famous work on the theory of information. In 1950 Fletcher and Galt published their theory of the articulation index, a theory that Fletcher had worked on for 30 years, which integrated his classic works on loudness and speech perception with models of speech intelligibility. In 1951 George Miller then wrote the first book Language and Communication, analyzing human speech communication with Claude Shannon's just published theory of information. Finally in 1955 George Miller published the first extensive analysis of phone decoding, in the form of confusion matrices, as a function of the speech-to-noise ratio. This work extended the Bell Labs' speech articulation studies with ideas from Shannon's Information theory. Both Miller and Fletcher showed that speech, as a code, is incredibly robust to mangling distortions of filtering and noise. Regrettably much of this early work was forgotten. While the key science of information theory blossomed, other than the work of George Miller, it was rarely applied to aural speech research. The robustness of speech, which is the most amazing thing about the speech code, has rarely been studied. It is my belief (i.e., assumption) that we can analyze speech intelligibility with the scientific method. The quantitative analysis of speech intelligibility requires both science and art. The scientific component requires an error analysis of spoken communication, which depends critically on the use of statistics, information theory, and psychophysical methods. The artistic component depends on knowing how to restrict the problem in such a way that progress may be made. It is critical to tease out the relevant from the irrelevant and dig for the key issues. This will focus us on the decoding of nonsense phonemes with no visual component, which have been mangled by filtering and noise. This monograph is a summary and theory of human speech recognition. It builds on and integrates the work of Fletcher, Miller, and Shannon. The long-term goal is to develop a quantitative theory for predicting the recognition of speech sounds. In Chapter 2 the theory is developed for maximum entropy (MaxEnt) speech sounds, also called nonsense speech. In Chapter 3, context is factored in. The book is largely reflective, and quantitative, with a secondary goal of providing an historical context, along with the many deep insights found in these early works.

Table of Contents:
Introduction.- Articulation.- Intelligibility.- Discussion with Historical Context.

About the Author :
​Jont B. Allen received his B.S. in electrical engineering from the University of Illinois, Urbana-Champaign, in 1966, and his M.S. and Ph.D. in electrical engineering from the University of Pennsylvania in 1968 and 1970, respectively. After graduation he joined Bell Laboratories, and was in the Acoustics Research Department in Murray Hill, NJ, from 1974–1996, as a distinguished member of technical staff. Since 1996 Dr. Allen has been a Technology Leader at AT&T Labs-Research. Since Aug. 2003, Allen is an Associate Professor in ECE, at the University of Illinois, and on the research staff of the Beckman Inst., Urbana IL. During his 32 year AT&T Bell Labs (and later AT&T Labs) career Dr. Allen has specialized in auditory signal processing. In the last 10 years he has concentrated on the problem of human speech recognition. His expertise spans the areas of signal processing, physical acoustics, cochlearmodeling, auditory neurophysiology, auditory psychophysics, and human speech recognition. Dr. Allen is a fellow (May 1981) of the Acoustical Society of America (ASA) and fellow ( January 1985) of the Institute of Electrical and Electronic Engineers (IEEE). In 1986 he was awarded the IEEE Acoustics Speech and Signal Processing (ASSP) Society Meritorious Service Award, and in 2000 received an IEEE Third Millennium Medal. He is a past member of the Executive Council of the ASA, the Administration Committee (ADCOM) of the IEEE ASSP, has served as Editor of the ASSP Transactions, as Chairman of the Publication Board of the ASSP Society, as General Chairman of the International Conference on ASSP (ICASSP-1988), and on numerous committees of both the ASA and the ASSP. He is presently a member of ASA Publications Policy Board. He has organized several workshops and 124 THE AUTHOR conferences on hearing research and signal processing. In 1984 he received funding from NIH to host the 2d International Mechanics of Hearing Workshop. He has a strong interest in electronic publications and has produced several CDROM publications, including suggesting and then overseeing technical details of the publication of the J. Acoust. Soc. Am. in DjVu format, and developed the first subject classification system for the IEEE Transactions of the ASSP, as well as the ASSP Magazine. In 1986–88 Dr. Allen participated in the development of the AT&T multiband compression hearing aid, later sold under the ReSound and Danavox name, and served as a member of the ReSound and SoundID Scientific advisory boards. In 1990 he was an Osher Fellow at the Exploratorium museum in San Francisco. In 1991–92 he served as an International Distinguished Lecturer for the IEEE Signal Processing Society. In 1993 he served on the Dean’s Advisory Council at the University of Pennsylvania. In 1994 he spent 5 weeks as Visiting Scientist and Distinguished Lecturer at the University of Calgary. Since 1987 he has been an Adjunct Associate Research Scientist in the Department of Otolaryngology at Columbia University, and on the CUNY speech and Hearing Faculty (Adjunct). In 2000 he received the IEEE Millennium Award, and in 2004, an IBM faculty award. Dr. Allen has more than 90 publications (36 peer reviewed) and 16 patents in the areas of speech noise reduction, speech and audio coding, and hearing aids.