The communication field is evolving rapidly in order to keep up with society's demands. As such, it becomes imperative to research and report recent advancements in computational intelligence as it applies to communication networks. The Handbook of Research on Recent Developments in Intelligent Communication Application is a pivotal reference source for the latest developments on emerging data communication applications. Featuring extensive coverage across a range of relevant perspectives and topics, such as satellite communication, cognitive radio networks, and wireless sensor networks, this book is ideally designed for engineers, professionals, practitioners, upper-level students, and academics seeking current information on emerging communication networking trends.

Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using electroencephalograms (EEGs) to detect and recognize different emotions. By incorporating these methods in brain-computer interface (BCI), we can achieve more natural, efficient communication between humans and computers. This book discusses how emotional states can be recognized in EEG images, and how this is useful for BCI applications. EEG and speech processing methods are explored, as are the technological basics of how to operate and record EEGs. Finally, the authors include information on EEG-based emotion recognition, classification, and a proposed EEG/speech fusion method for how to most accurately detect emotional states in EEG recordings.

The unique research area of audio-visual speech recognition has attracted much interest in recent years as visual information about lip dynamics has been shown to improve the performance of automatic speech recognition systems, especially in noisy environments.""Visual Speech Recognition: Lip Segmentation and Mapping"" presents an up-to-date account of research done in the areas of lip segmentation, visual speech recognition, and speaker identification and verification. A useful reference for researchers working in this field, this book contains the latest research results from renowned experts with in-depth discussion on topics such as visual speaker authentication, lip modeling, and systematic evaluation of lip features.

Current speech recognition systems are based on speaker independent speech models and suffer from inter-speaker variations in speech signal characteristics. This work develops an integrated approach for speech and speaker recognition in order to gain space for self-learning opportunities of the system. This work introduces a reliable speaker identification which enables the speech recognizer to create robust speaker dependent models In addition, this book gives a new approach to solve the reverse problem, how to improve speech recognition if speakers can be recognized. The speaker identification enables the speaker adaptation to adapt to different speakers which results in an optimal long-term adaptation.

Spoken dialog systems have the potential to offer highly intuitive user interfaces, as they allow systems to be controlled using natural language. However, the complexity inherent in natural language dialogs means that careful testing of the system must be carried out from the very beginning of the design process. This book examines how user models can be used to support such early evaluations in two ways: by running simulations of dialogs, and by estimating the quality judgments of users. First, a design environment supporting the creation of dialog flows, the simulation of dialogs, and the analysis of the simulated data is proposed. How the quality of user simulations may be quantified with respect to their suitability for both formative and summative evaluation is then discussed. The remainder of the book is dedicated to the problem of predicting quality judgments of users based on interaction data. New modeling approaches are presented, which process the dialogs as sequences, and which allow knowledge about the judgment behavior of users to be incorporated into predictions. All proposed methods are validated with example evaluation studies.

In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here.

The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent.

The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.

Proactive Spoken Dialogue Interaction in Multi-Party Environments describes spoken dialogue systems that act as independent dialogue partners in the conversation with and between users. The resulting novel characteristics such as proactiveness and multi-party capabilities pose new challenges on the dialogue management component of such a system and require the use and administration of an extensive dialogue history. In order to assist the proactive spoken dialogue systems development, a comprehensive data collection seems mandatory and may be performed in a Wizard-of-Oz environment. Such an environment builds also the appropriate basis for an extensive usability and acceptance evaluation.

Proactive Spoken Dialogue Interaction in Multi-Party Environments is a useful reference for students and researchers in speech processing.

The accurate determination of the speech spectrum, particularly for short frames, is commonly pursued in diverse areas including speech processing, recognition, and acoustic phonetics. With this book the author makes the subject of spectrum analysis understandable to a wide audience, including those with a solid background in general signal processing and those without such background. In keeping with these goals, this is not a book that replaces or attempts to cover the material found in a general signal processing textbook. Some essential signal processing concepts are presented in the first chapter, but even there the concepts are presented in a generally understandable fashion as far as is possible. Throughout the book, the focus is on applications to speech analysis; mathematical theory is provided for completeness, but these developments are set off in boxes for the benefit of those readers with sufficient background. Other readers may proceed through the main text, where the key results and applications will be presented in general heuristic terms, and illustrated with software routines and practical "show-and-tell" discussions of the results. At some points, the book refers to and uses the implementations in the Praat speech analysis software package, which has the advantages that it is used by many scientists around the world, and it is free and open source software. At other points, special software routines have been developed and made available to complement the book, and these are provided in the Matlab programming language. If the reader has the basic Matlab package, he/she will be able to immediately implement the programs in that platform---no extra "toolboxes" are required.

Speech Processing has rapidly emerged as one of the most widespread and well-understood application areas in the broader discipline of Digital Signal Processing. Besides the telecommunications applications that have hitherto been the largest users of speech processing algorithms, several non-traditional embedded processor applications are enhancing their functionality and user interfaces by utilizing various aspects of speech processing.

"Speech Processing in Embedded Systems" describes several areas of speech processing, and the various algorithms and industry standards that address each of these areas. The topics covered include different types of Speech Compression, Echo Cancellation, Noise Suppression, Speech Recognition and Speech Synthesis. In addition this book explores various issues and considerations related to efficient implementation of these algorithms on real-time embedded systems, including the role played by processor CPU and peripheral functionality.

This book describes the basic principles underlying the generation, coding and transmission of speech and audio signals and reveals the latest advances in this area. Waveform coding and parametric coding of speech are described and the fundamental principles behind these methods are delineated. Examples of speech coding standards in use today and their practical implementation are discussed. The principles underlying speech enhancement and speech recognition are also presented, along with the latest recent advances in these areas.

Spoken Dialogue Systems Technology and Design covers key topics in the field of spoken language dialogue interaction from a variety of leading researchers. It brings together several perspectives in the areas of corpus annotation and analysis, dialogue system construction, as well as theoretical perspectives on communicative intention, context-based generation, and modelling of discourse structure. These topics are all part of the general research and development within the area of discourse and dialogue with an emphasis on dialogue systems; corpora and corpus tools and semantic and pragmatic modelling of discourse and dialogue.

This book provides a survey of the state-of-the-art in the practical implementation of Spoken Dialog Systems for applications in everyday settings. It includes contributions on key topics in situated dialog interaction from a number of leading researchers and offers a broad spectrum of perspectives on research and development in the area. In particular, it presents applications in robotics, knowledge access and communication and covers the following topics: dialog for interacting with robots; language understanding and generation; dialog architectures and modeling; core technologies; and the analysis of human discourse and interaction. The contributions are adapted and expanded contributions from the 2014 International Workshop on Spoken Dialog Systems (IWSDS 2014), where researchers and developers from industry and academia alike met to discuss and compare their implementation experiences, analyses and empirical findings.

Designing Human Interface in Speech Technology bridges a gap between the needs of the technical engineer and cognitive researchers working in the multidisciplinary area of speech technology applications. The approach is systematic and the focus is on the utility of developing and designing speech related products.

Included is coverage of topics such as neuroscience on the multimodal cortex, cognitive theories on multi-task performance, stress and workload, as well as human information process theory and ecological interface design theory for evaluating speech-related human-system interfaces.

Of special emphasis are topics such as spoken dialogue system design, in-vehicle communication system design and speech technology in military applications. Also included are tools on how to analyze the design, different design theories and process, methods about how to understand users. The material systematically describes the user-center design process and usability evaluation methods.

Designing Human Interface in Speech Technology is appropriate for designers, engineers, and decision makers working in the area of speech technology research. It is also a good text book for senior university students and postgraduate students in the respective interaction design areas.

This thesis discusses the privacy issues in speech-based applications such as biometric authentication, surveillance, and external speech processing services. Author Manas A. Pathak presents solutions for privacy-preserving speech processing applications such as speaker verification, speaker identification and speech recognition. The author also introduces some of the tools from cryptography and machine learning and current techniques for improving the efficiency and scalability of the presented solutions. Experiments with prototype implementations of the solutions for execution time and accuracy on standardized speech datasets are also included in the text. Using the framework proposed may now make it possible for a surveillance agency to listen for a known terrorist without being able to hear conversation from non-targeted, innocent civilians."

Dialect Accent Features for Establishing Speaker Identity: A Case Study discusses the subject of forensic voice identification and speaker profiling. Specifically focusing on speaker profiling and using dialects of the Hindi language, widely used in India, the authors have contributed to the body of research on speaker identification by using accent feature as the discriminating factor. This case study contributes to the understanding of the speaker identification process in a situation where unknown speech samples are in different language/dialect than the recording of a suspect. The authors' data establishes that vowel quality, quantity, intonation and tone of a speaker as compared to Khariboli (standard Hindi) could be the potential features for identification of dialect accent.

While the use of technology to compensate for individual shortcomings is nothing new, there has been tremendous progress in the application of technology toward assisting individuals with disabilities, particularly with the use of computer synthesized speech (CSS) to help speech impaired people communicate using voice. Computer Synthesized Speech Technologies: Tools for Aiding Impairment provides information to current and future practitioners that will allow them to better assist speech disabled individuals who wish to utilize CSS technology. Just as important as the practitioner's knowledge of the latest advances in speech technology, so, too, is the practitioner's understanding of how specific client needs affect the use of CSS, how cognitive factors related to comprehension of CSS affect its use, and how social factors related to perceptions of the CSS user affect their interaction with others. This cutting edge book addresses those topics pertinent to understanding the myriad of concerns involved with the implementation of CSS so that CSS technologies may continue to evolve and improve for speech impaired individuals.

This book provides various speech enhancement algorithms for digital hearing aids. It covers information on noise signals extracted from silences of speech signal. The description of the algorithm used for this purpose is also provided. Different types of adaptive filters such as Least Mean Squares (LMS), Normalized LMS (NLMS) and Recursive Lease Squares (RLS) are described for noise reduction in the speech signals. Different types of noises are taken to generate noisy speech signals, and therefore information on various noises signals is provided. The comparative performance of various adaptive filters for noise reduction in speech signals is also described. In addition, the book provides a speech enhancement technique using adaptive filtering and necessary frequency strength enhancement using wavelet transform as per the requirement of audiogram for digital hearing aids. Presents speech enhancement techniques for improving performance of digital hearing aids; Covers various types of adaptive filters and their advantages and limitations; Provides a hybrid speech enhancement technique using wavelet transform and adaptive filters.

This work addresses the evaluation of the human and the automatic speaker recognition performances under different channel distortions caused by bandwidth limitation, codecs, and electro-acoustic user interfaces, among other impairments. Its main contribution is the demonstration of the benefits of communication channels of extended bandwidth, together with an insight into how speaker-specific characteristics of speech are preserved through different transmissions. It provides sufficient motivation for considering speaker recognition as a criterion for the migration from narrowband to enhanced bandwidths, such as wideband and super-wideband.

This book presents details of a text-to-speech synthesis procedure using epoch synchronous overlap add (ESOLA), and provides a solution for development of a text-to-speech system using minimum data resources compared to existing solutions. It also examines most natural speech signals including random perturbation in synthesis. The book is intended for students, researchers and industrial practitioners in the field of text-to-speech synthesis.

In this book, a novel approach that combines speech-based emotion recognition with adaptive human-computer dialogue modeling is described. With the robust recognition of emotions from speech signals as their goal, the authors analyze the effectiveness of using a plain emotion recognizer, a speech-emotion recognizer combining speech and emotion recognition, and multiple speech-emotion recognizers at the same time. The semi-stochastic dialogue model employed relates user emotion management to the corresponding dialogue interaction history and allows the device to adapt itself to the context, including altering the stylistic realization of its speech. This comprehensive volume begins by introducing spoken language dialogue systems and providing an overview of human emotions, theories, categorization and emotional speech. It moves on to cover the adaptive semi-stochastic dialogue model and the basic concepts of speech-emotion recognition. Finally, the authors show how speech-emotion recognizers can be optimized, and how an adaptive dialogue manager can be implemented. The book, with its novel methods to perform robust speech-based emotion recognition at low complexity, will be of interest to a variety of readers involved in human-computer interaction.

This book presents recent advances in nonlinear speech processing beyond nonlinear techniques. It shows that it exploits heuristic and psychological models of human interaction in order to succeed in the implementations of socially believable VUIs and applications for human health and psychological support. The book takes into account the multifunctional role of speech and what is "outside of the box" (see Bjoern Schuller's foreword). To this aim, the book is organized in 6 sections, each collecting a small number of short chapters reporting advances "inside" and "outside" themes related to nonlinear speech research. The themes emphasize theoretical and practical issues for modelling socially believable speech interfaces, ranging from efforts to capture the nature of sound changes in linguistic contexts and the timing nature of speech; labors to identify and detect speech features that help in the diagnosis of psychological and neuronal disease, attempts to improve the effectiveness and performance of Voice User Interfaces, new front-end algorithms for the coding/decoding of effective and computationally efficient acoustic and linguistic speech representations, as well as investigations capturing the social nature of speech in signaling personality traits, emotions and improving human machine interactions.

The book presents the history of time-domain representation and the extent of its development along with that of spectral domain representation in the cognitive and technology domains. It discusses all the cognitive experiments related to this development, along with details of technological developments related to both automatic speech recognition (ASR) and text to speech synthesis (TTS), and introduces a viable time-domain representation for both objective and subjective analysis, as an alternative to the well-known spectral representation. The book also includes a new cohort study on the use of lexical knowledge in ASR. India has numerous official dialects, and spoken-language technology development is a burgeoning area. In fact TTS and ASR taken together constitute the most important technology for empowering people. As such, the book describes time domain representation in such a way that it can be easily and seamlessly incorporated into ASR and TTS research and development. In short, it is a valuable guidebook for the development of ASR and TTS in all the Indian Standard Dialects using signal domain parameters.

Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and Maximum A-Posteriori (MAP) to adapt existing phonemic MSA acoustic models with a small amount of dialectal ECA speech data. Speech recognition results indicate a significant increase in recognition accuracy compared to a baseline model trained with only ECA data.