The Model Speaker


Book Description

Reprint of the original, first published in 1871. The publishing house Anatiposi publishes historical books as reprints. Due to their age, these books may have missing pages or inferior quality. Our aim is to preserve these books and make them available to the public so that they do not get lost.




Fundamentals of Speaker Recognition


Book Description

An emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks, call centres and other enterprise businesses for business process automation. "Fundamentals of Speaker Recognition" introduces Speaker Identification, Speaker Verification, Speaker (Audio Event) Classification, Speaker Detection, Speaker Tracking and more. The technical problems are rigorously defined, and a complete picture is made of the relevance of the discussed algorithms and their usage in building a comprehensive Speaker Recognition System. Designed as a textbook with examples and exercises at the end of each chapter, "Fundamentals of Speaker Recognition" is suitable for advanced-level students in computer science and engineering, concentrating on biometrics, speech recognition, pattern recognition, signal processing and, specifically, speaker recognition. It is also a valuable reference for developers of commercial technology and for speech scientists. Please click on the link under "Additional Information" to view supplemental information including the Table of Contents and Index.







The Competent Public Speaker


Book Description

Based on the National Communication Association's conceptual model for teaching and evaluating undergraduate public speeches (as developed by the author and others), Sherwyn P. Morreale offers a highly accessible, easy-to-teach, easy-to-learn approach to public speaking. The approach adopted in the text includes eight public speaking competencies - four on speech preparation and four on speech delivery - which are enhanced by emphasizing the impact of technology, ethics, culture, and diversity on public speaking. A number of unique features designed to improve teaching and learning include: - Students used as examples in each chapter so that readers can follow them as they learn about public speaking; - Tables and boxed text to reinforce the most important learning points; - Checkpoint and self-assessment tools so that readers can determine their level of competence and find out whether they are ready to proceed to the next chapter; - Competence-building activities for students to apply chapter concepts and practice public speaking strategies in the classroom or as take-home assignments; - An accompanying website which is updated on a regular basis and offers a forum for students to contact the author. Designed for introductory-level public speaking courses taught at two- and four-year colleges and universities, this text offers a distinctively practical alternative for students and teachers to achieve consistency across multiple sections of the public speaking course. An instructor's manual is available on request.




The Referable Speaker


Book Description

Use the gigs you get to get the gigs you want. You spend a ton of time building your personal brand to generate more speaking opportunities. You write a blog, record podcasts, post on Instagram, and upload to YouTube. You refine your speaking website, work on that book, participate in Clubhouse, and comment on LinkedIn. You share your expertise and insight freely. All of that hard work might get you one gig. And, unfortunately, none of those things will guarantee you the next gig. But what if you became a referable speaker? In this ground-breaking guide to building a speaking career, New York Times bestselling author Michael Port, co-founder of Heroic Public Speaking, teams up with bestselling author and world-renowned keynote speaker Andrew Davis to show you the fastest, most practical way to increase your fee and generate more leads. Discover precisely how event organizers select their keynote speakers, what you can do to win them over, and even how to set your fee. Port and Davis show you why you need to stop investing in marketing yourself as a great speaker and start investing in your speech. Because, unless you're famous, event organizers won't buy you (or your personal brand). They'll buy your speech, then your idea, then you―in that order. You'll learn exactly how 81 speakers built sustainable speaking revenues by evaluating the three F+E+E Factors and 10 sub-factors-factors that turn novice presenters into transformational keynote speakers. And you'll evaluate how to make the most meaningful impact through 58 professional speaker case studies based on six years of industry data. See how elegantly simple it is to make the leap from breakout rooms to the keynote stage. You'll leave with an entirely new, eye-opening, and refreshing understanding of how the speaking business really works and how you can make an impact fast. Do you have what it takes to become a referable speaker? You do. Go ahead, take a look inside!




Machine Learning for Speaker Recognition


Book Description

Learn fundamental and advanced machine learning techniques for robust speaker recognition and domain adaptation with this useful toolkit.




Speaker Classification II


Book Description

This two-volume set constitutes a state-of-the-art survey in the field of speaker classification, addressing many critical questions. The twenty-two articles of the second volume cover a number of areas, including gender recognition systems, emotion recognition, text-dependent speaker verification systems, an analysis of both speaker and verbal content information, and accent identification.







Automatic Speech and Speaker Recognition


Book Description

Research in the field of automatic speech and speaker recognition has made a number of significant advances in the last two decades, influenced by advances in signal processing, algorithms, architectures, and hardware. These advances include: the adoption of a statistical pattern recognition paradigm; the use of the hidden Markov modeling framework to characterize both the spectral and the temporal variations in the speech signal; the use of a large set of speech utterance examples from a large population of speakers to train the hidden Markov models of some fundamental speech units; the organization of speech and language knowledge sources into a structural finite state network; and the use of dynamic, programming based heuristic search methods to find the best word sequence in the lexical network corresponding to the spoken utterance. Automatic Speech and Speaker Recognition: Advanced Topics groups together in a single volume a number of important topics on speech and speaker recognition, topics which are of fundamental importance, but not yet covered in detail in existing textbooks. Although no explicit partition is given, the book is divided into five parts: Chapters 1-2 are devoted to technology overviews; Chapters 3-12 discuss acoustic modeling of fundamental speech units and lexical modeling of words and pronunciations; Chapters 13-15 address the issues related to flexibility and robustness; Chapter 16-18 concern the theoretical and practical issues of search; Chapters 19-20 give two examples of algorithm and implementational aspects for recognition system realization. Audience: A reference book for speech researchers and graduate students interested in pursuing potential research on the topic. May also be used as a text for advanced courses on the subject.




Robust Speaker Recognition in Noisy Environments


Book Description

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.