Mechanisms of Speech Recognition explores the mechanisms underlying speech recognition. Topics covered include the auditory system, speech production, auditory psychophysics, speech synthesis and analysis, vowel and consonant recognition, and perception of prosodic features and of distorted speech. Automatic speech recognition and models of speech recognition are also given consideration. This volume consists of 11 chapters and begins with an overview of speech recognition, communication, and production. More specifically, it examines the way in which the organs of the vocal apparatus are employed to transform a message consisting of a string of linguistic units, such as words or phonemes, into a wave of continuous sounds which are recognized as speech. The auditory system and its parts are then described, from the ears to the organ of Corti and nerve cells. The chapters that follow focus on the behavior of the hearing system, the various techniques of analyzing speech sounds, and speech synthesizers such as vocoders. The mechanisms underlying the recognition of vowels and consonants are also described, along with the physical parameters of the speech wave which signal the prosody of an utterance, the effects of distortions in the speech wave on speech perception, and tools used in automatic speech recognition. The book concludes with an evaluation of models of speech recognition. This book will be of interest to phoneticians, linguists, physiologists, psychologists, and physicists.

Describes the acoustics of speech production & the mechanisms of the ear. Introduces psychological techniques to show the sensitivity & limits of hearing. Describes methods of analysing & synthesizing speech sounds. Gives an introduction to the machine recognition of speech.

Although speech is the primary behavioral medium by which humans communicate, its auditory basis is poorly understood, having profound implications on efforts to ameliorate the behavioral consequences of hearing impairment and on the development of robust algorithms for computer speech recognition. In this volume, the authors provide an up-to-date synthesis of recent research in the area of speech processing in the auditory system, bringing together a diverse range of scientists to present the subject from an interdisciplinary perspective. Of particular concern is the ability to understand speech in uncertain, potentially adverse acoustic environments, currently the bane of both hearing aid and speech recognition technology. There is increasing evidence that the perceptual stability characteristic of speech understanding is due, at least in part, to elegant transformations of the acoustic signal performed by auditory mechanisms. As a comprehensive review of speech's auditory basis, this book will interest physiologists, anatomists, psychologists, phoneticians, computer scientists, biomedical and electrical engineers, and clinicians.

Perceptual categorization is fundamental to the brain’s remarkable ability to process large amounts of sensory information and efficiently recognize objects including speech. Perceptual categorization is the neural bridge between lower-level sensory and higher-level language processing. A long line of research on the physical properties of the speech signal as determined by the anatomy and physiology of the speech production apparatus has led to descriptions of the acoustic information that is used in speech recognition (e.g., stop consonants place and manner of articulation, voice onset time, aspiration). Recent research has also considered what visual cues are relevant to visual speech recognition (i.e., the visual counter-parts used in lipreading or audiovisual speech perception). Much of the theoretical work on speech perception was done in the twentieth century without the benefit of neuroimaging technologies and models of neural representation. Recent progress in understanding the functional organization of sensory and association cortices based on advances in neuroimaging presents the possibility of achieving a comprehensive and far reaching account of perception in the service of language. At the level of cell assemblies, research in animals and humans suggests that neurons in the temporal cortex are important for encoding biological categories. On the cellular level, different classes of neurons (interneurons and pyramidal neurons) have been suggested to play differential roles in the neural computations underlying auditory and visual categorization. The moment is ripe for a research topic focused on neural mechanisms mediating the emergence of speech representations (including auditory, visual and even somatosensory based forms). Important progress can be achieved by juxtaposing within the same research topic the knowledge that currently exists, the identified lacunae, and the theories that can support future investigations. This research topic provides a snapshot and platform for discussion of current understanding of neural mechanisms underlying the formation of perceptual categories and their relationship to language from a multidisciplinary and multisensory perspective. It includes contributions (reviews, original research, methodological developments) pertaining to the neural substrates, dynamics, and mechanisms underlying perceptual categorization and their interaction with neural processes governing speech perception.

Explains the basic mechanisms involved in spoken communication, merging the field of speech pathology, communications, psychology, engineering, and computer science.

Perceptual processes mediating recognition, including the recognition of objects and spoken words, is inherently multisensory. This is true in spite of the fact that sensory inputs are segregated in early stages of neuro-sensory encoding. In face-to-face communication, for example, auditory information is processed in the cochlea, encoded in auditory sensory nerve, and processed in lower cortical areas. Eventually, these “sounds” are processed in higher cortical pathways such as the auditory cortex where it is perceived as speech. Likewise, visual information obtained from observing a talker’s articulators is encoded in lower visual pathways. Subsequently, this information undergoes processing in the visual cortex prior to the extraction of articulatory gestures in higher cortical areas associated with speech and language. As language perception unfolds, information garnered from visual articulators interacts with language processing in multiple brain regions. This occurs via visual projections to auditory, language, and multisensory brain regions. The association of auditory and visual speech signals makes the speech signal a highly “configural” percept. An important direction for the field is thus to provide ways to measure the extent to which visual speech information influences auditory processing, and likewise, assess how the unisensory components of the signal combine to form a configural/integrated percept. Numerous behavioral measures such as accuracy (e.g., percent correct, susceptibility to the “McGurk Effect”) and reaction time (RT) have been employed to assess multisensory integration ability in speech perception. On the other hand, neural based measures such as fMRI, EEG and MEG have been employed to examine the locus and or time-course of integration. The purpose of this Research Topic is to find converging behavioral and neural based assessments of audiovisual integration in speech perception. A further aim is to investigate speech recognition ability in normal hearing, hearing-impaired, and aging populations. As such, the purpose is to obtain neural measures from EEG as well as fMRI that shed light on the neural bases of multisensory processes, while connecting them to model based measures of reaction time and accuracy in the behavioral domain. In doing so, we endeavor to gain a more thorough description of the neural bases and mechanisms underlying integration in higher order processes such as speech and language recognition.

A wide range of fields of study support speech research. They cover many fields like for instance phonetics, linguistics, psychology, cognitive science, sonics, information engineering (information theory, pattern recognition, artificial intelligence), and it is an extremely difficult job to carry all of these in one body.The first half of this book gives detailed descriptions of engineering applications, that is the speech, hearing and perception mechanisms that form the basis for automatic synthesis and recognition of speech. The second half of this book gives a detailed explanation of speech synthesis and recognition based on a collective physiological approach, that is the artificial neural networks which imitate human neural networks and have once again been bathed in attention lately. The characteristics of this book are that, along with having engineers and technicians as its main targets, it explains engineering models based on speech science.

Phonetically reduced forms are plentiful, theoretically interesting, and a key challenge for automatic speech recognition systems. Yet canonical forms are still central to models of production and perception. Drawing from different fields and diverse languages, this volume brings new insights to the debate on abstractions and canonical forms in linguistics: their psychological reality, descriptive adequacy, and technical implementability.