Bücher der Reihe SpringerBriefs in Speech Technology

This book discusses digital audio watermarking copyright assurance. The author first outlines the topic of watermarking data that can be used for copyright assurance that incorporates text messages, copyright audio, handwritten text, logo and cell phone numbers.

This book explains speech enhancement in the Fractional Fourier Transform (FRFT) domain and investigates the use of different FRFT algorithms in both single channel and multi-channel enhancement systems, which has proven to be an ideal time frequency analysis tool in many speech signal processing applications.

Dialect Accent Features for Establishing Speaker Identity: A Case Study discusses the subject of forensic voice identification and speaker profiling.

This book introduces audio watermarking methods in transform domain based on matrix decomposition for copyright protection. Chapter 1 discusses the application and properties of digital watermarking. Chapter 2 proposes a blind lifting wavelet transform (LWT) based watermarking method using fast Walsh Hadamard transform (FWHT) and singular value decomposition (SVD) for audio copyright protection. Chapter 3 presents a blind audio watermarking method based on LWT and QR decomposition (QRD) for audio copyright protection. Chapter 4 introduces an audio watermarking algorithm based on FWHT and LU decomposition (LUD). Chapter 5 proposes an audio watermarking method based on LWT and Schur decomposition (SD). Chapter 6 explains in details on the challenges and future trends of audio watermarking in various application areas.Introduces audio watermarking methods for copyright protection and ownership protection;Describes watermarking methods with encryption and decryption that provide excellent performance in terms of imperceptibility, robustness, and data payload;Discusses in details on the challenges and future research direction of audio watermarking in various application areas.

This book presents a statistical parametric speech synthesis (SPSS) framework for developing a speech synthesis system where the desired speech is generated from the parameters of vocal tract and excitation source.

This book presents techniques for audio search, aimed to retrieve information from massive speech databases by using audio query words. The topics covered also include available databases, software / tools, patents / copyrights, and different platforms for benchmarking.

In this book, application-related studies for acoustic biomedical sensors are covered in depth. The book features an array of different biomedical signals, including acoustic biomedical signals as well as the thermal biomedical signals, magnetic biomedical signals, and optical biomedical signals to support healthcare.

This updated book expands upon prosody for recognition applications of speech processing. and presents methods for extraction and representation of prosody for applications such as speaker recognition, language recognition and speech recognition.

This book presents research and applications on arrival estimation and localization in speech processing to ensure that the broad vision of the direction of arrival estimation (DOAE) / localization of speech sources is well-established.

This book introduces audio watermarking methods for copyright protection, which has drawn extensive attention for securing digital data from unauthorized copying.

Guiding the reader through every aspect of the field, from design principles to infrastructure to effective fine-tuning strategies, this volume analyzes the extent to which research on academic spoken dialog systems converges with real-world applications.

Readers willbe able to understand the fundamentals of speech processing as well as theoptimization techniques, how the speech enhancement algorithms are implementedby utilizing optimization methods, and will be given the tools to develop newalgorithms.

This book discusses the Partially Observable Markov Decision Process (POMDP) framework applied in dialogue systems. Starting from scratch, they present the state, the transition model, the observation model and then finally the reward model from unannotated and noisy dialogues.

The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual;

Contemporary Methods for Speech Parameterization offers a general view of short-time cepstrum-based speech parameterization and provides a common ground for further in-depth studies on the subject.

This book explores the various categories of speech variation and works to draw a line between linguistic and paralinguistic phenomenon of speech.

This book explains how can be created information extraction (IE) applications that are able to tap the vast amount of relevant information available in natural language sources: Internet pages, official documents such as laws and regulations, books and newspapers, and social web.

This book presents state of art research in speech emotion recognition. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.

"Ultra Low Bit-Rate Speech Coding" focuses on the specialized topic of speech coding at very low bit-rates of 1 Kbits/sec and less, particularly at the lower ends of this range, down to 100 bps.

This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.

This book focuses on speech processing in the presence of low-bit rate coding and varying background environments. Accurate estimation of these crucial events will be useful for carrying out various speech tasks such as speech recognition, speaker recognition and speech rate modification in mobile environments.

"Phonetic Search Methods for Large Databases" focuses on Keyword Spotting (KWS) within large speech databases.

In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner.

Provides a survey of methods designed to aid clinicians in the diagnosis and monitoring of speech disorders such as dysarthria and dyspraxia, with an emphasis on the signal processing techniques, statistical validity of the results presented in the literature, and the appropriateness of methods that do not require specialized equipment.

"Emotion Recognition Using Speech Features" provides coverage of emotion-specific features present in speech. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models.

Predicting Prosody from Text for Text-to-Speech Synthesis covers the specific aspects of prosody, mainly focusing on how to predict the prosodic information from linguistic text, and then how to exploit the predicted prosodic knowledge for various speech applications.

Speech Processing and Soft Computing includes coverage of synergy between speech technology and bio-inspired soft computing methods.

The author covers the fundamentals of both information and communication security including current developments in some of the most critical areas of automatic speech recognition.

Cross-Word Modeling for Arabic Speech Recognition utilizes phonological rules in order to model the cross-word problem, a merging of adjacent words in speech caused by continuous speech, to enhance the performance of continuous speech recognition systems.