Speech Technology and Text Mining in Medicine and Health Care

This book offers an overview of some recent advances in the Computational Bioacoustics methods and technology. In the focus of discussion is the pursuit of scalability, which would facilitate real-world applications of different scope and purpose, such as wildlife monitoring, biodiversity assessment, pest population control, and monitoring the spread of disease transmitting mosquitoes. The various tasks of Computational Bioacoustics are described and a wide range of audio parameterization and recognition tasks related to the automated recognition of species and sound events is discussed. Many of the Computational Bioacoustics methods were originally developed for the needs of speech, audio, or image processing, and afterwards were adapted to the requirements of automated acoustic recognition of species, or were elaborated further to address the challenges of real-world operation in 24/7 mode. The interested reader is encouraged to follow the numerous references and links to web resources for further information and insights. This book is addressed to Software Engineers, IT experts, Computer Science researchers, Bioacousticians, and other practitioners concerned with the creation of new tools and services, aimed at enhancing the technological support to Computational Bioacoustics applications.

STTM, Speech Technology and Text Mining in Medicine and Health Care

This series demonstrates how the latest advances in speech technology and text mining positively affect patient healthcare and, in a much broader sense, public health at large. New developments in text mining methods have allowed health care providers to monitor a large population of patients at any time and from any location. Employing advanced summarization techniques, patient data can be readily extracted from extensive clinical documents in electronic health records and immediately made available to the physician. These same summarization techniques can also aid the healthcare provider in extracting from the large corpora of medical literature the relevant information for treating the patient. The series topics include the design and acceptance of speech-enabled robots that assist in the operating room, studies of signal processing and acoustic modeling for speech and communication disorders, advanced statistical speech enhancement methods for creating synthetic voice, and technologies for addressing speech and language impairments. Titles in the Series consist of both authored books and edited contributions. All authored books and contributed works are peer-reviewed. The Series is for speech scientists and speech engineers, machine learning experts, biomedical engineers, medical speech pathologists, linguists, and healthcare professionals

Signal and Acoustic Modeling for Speech and Communication Disorders demonstrates how speech signal processing and acoustic modeling can be instrumental in early detection and successful intervention with speech deficits resulting from Parkinson’s disease, Autism Spectrum disorder, cleft palate, intellectual disabilities, and neuro-motor impairments. Utilizing some of the most advanced methods in signal and acoustic modeling, this eminent group of contributors show how such technologies can inure to the benefit of healthcare and to society writ large. Paradoxically, what most of us take for granted still remains a Sisyphean battle for those with speech and language disorders, who struggle every day to make themselves heard and understood. The purpose of this book is to stimulate a vibrant discussion among speech scientists, system designers, and practitioners on how to best marshal the latest advances in signal and acoustic modeling to address some of the most challenging speech and communication disorders affecting a wide variety of patient populations across the world.

• Examines various speech technologies deployed in healthcare service robots to maximize the robot's ability to interpret user input.
• Demonstrates how robot anthropomorphic features and etiquette in behavior promotes user-positive emotions, acceptance of robots, and compliance with robot requests.
• Analyzes how multimodal medical-service robots and other cyber-physical systems can reduce mistakes and mishaps in the operating room.
• Evaluates various input methods for improving acceptance of robots in the older adult population.
• Presents case studies of cognitively and socially engaging robots in the long-term care setting for helping older adults with activities of daily living and in the pediatric setting for helping children with autism spectrum conditions and metabolic disorders.

Speech and Automata in Health Care forges new ground by closely analyzing how three separate disciplines - speech technology, robotics, and medical/surgical/assistive care - intersect with one another, resulting in an innovative way of diagnosing and treating both juvenile and adult illnesses and conditions. This includes the use of speech-enabled robotics to help the elderly population cope with common problems associated with aging caused by the diminution in their sensory, auditory and motor capabilities. By examining the emerging nexus of speech, automata, and health care, the authors demonstrate the exciting potential of automata, both speech-driven and multimodal, to affect the healthcare delivery system so that it better meets the needs of the populations it serves. This book provides both empirical research findings and incisive literature reviews that demonstrate some of the more novel uses of speech-enabled and multimodal automata in the operating room, hospital ward, long-term care facility, and in the home. Studies backed by major universities, research institutes, and by EU-funded collaborative projects are debuted in this volume.

This volume provides a wealth of timely material for industrial engineers, speech scientists, computational linguists, and for signal processing and intelligent systems design experts.

Topics include:

• Spoken Interaction with Healthcare Robots
• Service Robot Feature Effects on Patient Acceptance/Emotional Response
• Designing Embodied and Virtual Agents for the Operating Room
• The Emerging Role of Robotics for Personal Health Management in the Older-Adult Population
• Why Input Methods for Robots that Serve the Older Adult Are Critical for Usability
• Socially and Cognitively Engaging Robots in the Long-Term Care Setting
• Voice-Enabled Assistive Robots for Managing Autism Spectrum Conditions
• ASR and TTS for Voice-Controlled Robot Interactions in Treating Children with Metabolic Disorders

This book draws on the recent remarkable advances in speech and language processing: advances that have moved speech technology beyond basic applications such as medical dictation and telephone self-service to increasingly sophisticated and clinically significant applications aimed at complex speech and language disorders. The book provides an introduction to the basic elements of speech and natural language processing technology, and illustrates their clinical potential by reviewing speech technology software currently in use for disorders such as autism and aphasia. The discussion is informed by the authors' own experiences in developing and investigating speech technology applications for these populations. Topics include detailed examples of speech and language technologies in both remediative and assistive applications, overviews of a number of current applications, and a checklist of criteria for selecting the most appropriate applications for particular user needs.

This book will be of benefit to four audiences: application developers who are looking to apply these technologies; clinicians who are looking for software that may be of value to their clients; students of speech-language pathology and application development; and finally, people with speech and language disorders and their friends and family members.

• Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature.
• Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing.
• Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired.

Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information.

This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers.

Topics in this book include:
• Mining Biomedical Literature and Clinical Narratives
• Medication Information Extraction
• Machine Learning Techniques for Mining Medical Search Queries
• Detecting the Level of Personal Health Information Revealed in Social Media
• Curating Layperson’s Personal Experiences with Health Care from Social Media and Twitter
• Health Dialogue Systems for Improving Access to Online Content
• Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired
• Semantic-based Visual Information Retrieval for Mining Radiographic Image Data
• Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions

This book provides the reader with empirical findings on innovative signal processing approaches to detecting pathologies in infant cries, by comparing new technological approaches to standard ones. The contributors examine novel approaches to machine adaptation to dysarthric speech.