Bøger i SpringerBriefs in Speech Technology serien

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.

This book provides a survey on wide-spread of employing wavelets analysis in different applications of speech processing. The author examines development and research in different applications of speech processing. The book also summarizes the state of the art research on wavelet in speech processing.

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 provides an overview of a recent and flexible approach to speech synthesis design to develop the first statistical parametric speech synthesizer for Ibibio, a West African tonal language. The design precludes the inflexibility encountered when modeling tonal features of the language and can be used for other tonal African languages.

The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).

This book covers language modeling and automatic speech recognition for inflective languages (e.g. This is then presented through the analysis of errors in the system and the development of language models and their inclusion in speech recognition systems, which specifically address the errors that are relevant for targeted applications.

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.

Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features.

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.

This book provides a broad and comprehensive overview of the existing technical approaches in the area of silent speech interfaces (SSI), both in theory and in application.

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.