Speech recognition Books

Book SynopsisWe live in a society which is increasingly interconnected, in which communication between individuals is mostly mediated via some electronic platform, and transactions are often carried out remotely. In such a world, traditional notions of trust and confidence in the identity of those with whom we are interacting, taken for granted in the past, can be much less reliable. Biometrics - the scientific discipline of identifying individuals by means of the measurement of unique personal attributes - provides a reliable means of establishing or confirming an individual''s identity. These attributes include facial appearance, fingerprints, iris patterning, the voice, the way we write, or even the way we walk. The new technologies of biometrics have a wide range of practical applications, from securing mobile phones and laptops to establishing identity in bank transactions, travel documents, and national identity cards. This Very Short Introduction considers the capabilities of biometrics-based identity checking, from first principles to the practicalities of using different types of identification data. Michael Fairhurst looks at the basic techniques in use today, ongoing developments in system design, and emerging technologies, all aimed at improving precision in identification, and providing solutions to an increasingly wide range of practical problems. Considering how they may continue to develop in the future, Fairhurst explores the benefits and limitations of these pervasive and powerful technologies, and how they can effectively support our increasingly interconnected society.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.Table of Contents1: Are you who you say you are?2: Biometrics: where should I start?3: Making biometrics work4: Enhancing biometric processing5: An introduction to predictive biometrics6: Where are we going?Further readingIndex

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Book SynopsisDesign and implement voice user interfaces. This guide to VUI helps you make decisions as you deal with the challenges of moving from a GUI world to mixed-modal interactions with GUI and VUI. The way we interact with devices is changing rapidly and this book gives you a close view across major companies via real-world applications and case studies. Voice User Interface Design provides an explanation of the principles of VUI design. The book covers the design phase, with clear explanations and demonstrations of each design principle through examples of multi-modal interactions (GUI plus VUI) and how they differ from pure VUI. The book also differentiates principles of VUI related to chat-based bot interaction models. By the end of the book you will have a vision of the future, imagining new user-oriented scenarios and new avenues, which until now were untouched. What You''llTable of ContentsChapter 1: Introduction – What is VUI Chapter Goal: defines VUI, its history and present day technology No of pages 10 Sub -Topics 1. What is VUI? 2. When did it all start? 3. The journey 4. Current day Chapter 2: Modern day VUI landscape Chapter Goal: understanding how major players are going forward with their VUI and device strategy No of pages: 25 Sub - Topics 1. Major players and their unique positions 2. Direction towards world domination 3. Device strategy of major players 4. Integration of AR, VR, digital assistance Chapter 3: Principles of VUI Chapter Goal: laying down the guiding principles to create a delightful VUI No of pages : 70 - 150 Sub - Topics: 5. Principles with associated examples This might be broken down into 5 separate chapters. Chapter 4: Multi modal interaction Chapter Goal: understanding an ecosystem where different modes of interaction takes place across devices simultaneously. No of pages: 50 - 70 Sub - Topics: 1. GUI model and examples 2. GUI + VUI as a model with examples 3. VUI only as a model with examples 4 . Challenges Chapter 5: Future Ahead Chapter Goal: giving an idea of the plethora of use cases, scenarios where VUI will affect human lives. 1. An idea about future tech 2. Imagining a future case with the reader 3. Creating potential scenarios, solving for VUI

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Book SynopsisWhether you're designing a mobile app, a toy, or a device such as a home assistant, this practical book guides you through basic VUI design principles, helps you choose the right speech recognition engine, and shows you how to measure your VUI's performance and improve upon it.

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Book SynopsisTo create their own voice "skills," users need to learn some new device toolkits, the basics of Voice UI design, and some emerging best practices for building and deploying on these diverse platforms. Voice Applications for Alexa and Google Assistant guides readers in the exciting world of designing, building, and implementing voice-based applications for Amazon Alexa or Google Assistant! They learn how to build their own "skills"—the voice app term for actions the device can perform—from scratch. Key Features · Designing a voice interaction model · Fulfilling skills via a serverless platform like AWS Lambda · Connecting a skill to a database Audience Written for JavaScript developers interested in building voice-enabled applications. No prior experience required! Author Bio Dustin A. Coates is a web developer and web development instructor. He has taught hundreds of students online and offline at General Assembly. Dustin also developed popular courses for OneMonth.com and the European non-profit Konexio, which teaches refugees how to code.

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Book SynopsisVoice recognition is here at last. Alexa and other voice assistants have now become widespread and mainstream. Is your app ready for voice interaction? Learn how to develop your own voice applications for Amazon Alexa. Start with techniques for building conversational user interfaces and dialog management. Integrate with existing applications and visual interfaces to complement voice-first applications. The future of human-computer interaction is voice, and we'll help you get ready for it. For decades, voice-enabled computers have only existed in the realm of science fiction. But now the Alexa Skills Kit (ASK) lets you develop your own voice-first applications. Leverage ASK to create engaging and natural user interfaces for your applications, enabling them to listen to users and talk back. You'll see how to use voice and sound as first-class components of user-interface design. We'll start with the essentials of building Alexa voice applications, called skills, including useful tools for creating, testing, and deploying your skills. From there, you can define parameters and dialogs that will prompt users for input in a natural, conversational style. Integrate your Alexa skills with Amazon services and other backend services to create a custom user experience. Discover how to tailor Alexa's voice and language to create more engaging responses and speak in the user's own language. Complement the voice-first experience with visual interfaces for users on screen-based devices. Add options for users to buy upgrades or other products from your application. Once all the pieces are in place, learn how to publish your Alexa skill for everyone to use. Create the future of user interfaces using the Alexa Skills Kit today. What You Need: You will need a computer capable of running the latest version of Node.js, a Git client, and internet access.

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Book SynopsisSpeech represents the most natural means of communication between humans. By using Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems, machines also become able to interact with humans using speech. This is of particular importance for building interactive robots or speech-enabled chatbots. This book starts by exploring state-of-the-art ASR and TTS approaches, making use of artificial neural networks, relevant also to low-resource scenarios. Then, it explores the application of speech technology to specific domains, such as the medical domain, human-robot interaction, and even interlinking of speech and text resources using linguistic linked open data (LLOD) principles. The book also provides punctuation restoration techniques, enabling the production of high-quality text transcripts. Included algorithms have low latency and can be parallelized, thus enabling their use in interactive systems. Chapter authors are professors and scientific researchers with experience in building and using natural language processing algorithms and speech applications.

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Book SynopsisThe two-volume proceedings set LNAI 14338 and 14339 constitutes the refereed proceedings of the 25th International Conference on Speech and Computer, SPECOM 2023, held in Dharwad, India, during November 29–December 2, 2023.The 94 papers included in these proceedings were carefully reviewed and selected from 174 submissions. They focus on all aspects of speech science and technology: ​automatic speech recognition; computational paralinguistics; digital signal processing; speech prosody; natural language processing; child speech processing; speech processing for medicine; industrial speech and language technology; speech technology for under-resourced languages; speech analysis and synthesis; speaker and language identification, verification and diarization.Table of Contents​Automatic Speech Recognition.- Extreme Learning Layer: A Boost for Spoken Digit Recognition with Spiking Neural Networks.- EMO-AVSR: Two-Level Approach for Audio-Visual Emotional Speech Recognition.- Significance of Audio Quality in Speech-to-Text Translation Systems.- Everyday Conversations: a Comparative Study of Expert Transcriptions and ASR Outputs at a Lexical Level.- Improving Automatic Speech Recognition with Dialect-Specific Language Models.- Emotional speech recognition of Holocaust survivors with deep neural network models for Russian language.- Computational Paralinguistics.- Aggregation Strategies of Wav2vec 2.0 Embeddings for Computational Paralinguistic Tasks.- Rhythm Formant Analysis for Automatic Depression Classification.- Determining Alcohol Intoxication Based on Speech and Neural Networks.- Linear Frequency Residual Cepstral Coefficients for Speech Emotion Recognition.- Enhancing Stutter Detection in Speech using Zero Time Windowing Cepstral Coefficients and Phase Information.- Source and System-based Modulation Approach for Fake Speech Detection.- Digital Signal Processing.- Investigation of Different Calibration Methods for Deep Speaker Embedding based Verification Systems.- Learning to Predict Speech Intelligibility from Speech Distortions.- Sparse Representation Frameworks for Acoustic Scene Classification.- Driver Speech Detection in Real Driving Scenario.- Regularization based Incremental Learning in TCNN for Robust Speech Enhancement Targeting Effective Human Machine Interaction.- Candidate Speech Extraction from Multi-Speaker Single-Channel Audio Interviews.- Post-Processing of Translated Speech by Pole Modification and Residual Enhancement to Improve Perceptual Quality.- Region Normalized Capsule Network based Generative Adversarial Network for Non-Parallel Voice Conversion.- Speech Enhancement using LinkNet Architecture.- ATT:Adversarial Trained Transformer for Speech Enhancement.- Human Identification by Dynamics of Changes in Brain Frequencies Using Artificial Neural Networks.- Speech Prosody.- Analysis of Formant Trajectories of a Speech Signal for the Purpose of Forensic Identification of a Foreign Speaker.- Gestures vs. Prosodic Structure in Laboratory Ironic Speech.- Sounds of < sil > ence: Acoustics of Inhalation in Read Speech.- Prolongations as Hesitation Phenomena in Spoken Speech in First and Second Language.- Study of Indian English Pronunciation Variabilities Relative to Received Pronunciation.- Multimodal Collaboration in Expository Discourse: Verbal and Nonverbal Moves Alignment.- Association of Time Domain Features with Oral Cavity Configuration during Vowel Production and its Application in Vowel Recognition.- Prosodic Interaction Models in a Conversation.- Natural Language Processing.- Development and Research of Dialogue Agents with Long-Term Memory and Web Search.- Pre- and Post-Textual Contexts in Assessment of a Message as Offensive or Defensive Aggression Verbalization.- Boosting Rule-based Grapheme-to-Phoneme Conversion with Morphological Segmentation and Syllabification in Bengali.- Revisiting Assessment of Text Complexity: Lexical and Syntactic Parameters Fluctuations.- Analysis of Natural Language Understanding Systems with L2 Learner Specific Synthetic Grammatical Errors based on Parts-of-Speech.- On the Most Frequent Sequences of Words in Russian Spoken Everyday Language (Bigrams and Trigrams): An Experience of Classification.- Child Speech Processing.- Recognition of the Emotional State of Children by Video and Audio Modalities by Indian and Russian Experts.- Effect of Linear Prediction Order to Modify Formant Locations for Children Speech Recognition.- Gammatone-Filterbank based Pitch-Normalized Cepstral Coefficients for Zero-Resource Children’s ASR.- System Assisted Vocal Response Analysis and Assessment of Autism in Children: A Machine Learning Based Approach.- Addressing Effects of Formant Dispersion and Pitch Sensitivity for the Development of Children’s KWS System.- Development of Children’s KWS System Perceptual Experiment and Automatic Recognition by Video, Audio and Text Modalities.- Linear Frequency Residual Features for Infant Cry Classification.- Speech Processing for Medicine.- Identification of Voice Disorders: A Comparative Study of Machine Learning Algorithms.- Transfer Learning using Whisper for Dysarthric Automatic Speech Recognition.- Significance of Duration Modification in Reducing Listening Effort of Slurred Speech from Patients with Traumatic Brain Injury.- Significance of Duration Modification in Reducing Listening Effort of Slurred Speech from Patients with Traumatic Brain Injury.- Respiratory Sickness Detection from Audio Recordings using CLIP Models.- Investigating the Effect of Data Impurity on the Detection Performances of Mental Disorders through Spoken Dialogues.

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Book SynopsisImmer mehr Unternehmen bauen Chatbots, damit ihre Kunden und Mitarbeiter in natürlicher Sprache mit den Systemen des Unternehmens kommunizieren können. Mittels Chatbots können dialogintensive Prozesse automatisiert und neue Wissensquellen erschlossen werden. Das vorliegende essential führt die Grundlagen von Chatbots ein und zeigt mit Praxisbeispielen der Schweizerischen Post, wo sie angewendet werden können, worauf bei ihrer Gestaltung geachtet werden muss und welche neuen Fähigkeiten in einem Unternehmen für deren Einsatz erforderlich sind.Die Autoren:Toni Stucki hat langjährige Erfahrungen als Softwarearchitekt. Bei der Schweizerischen Post leitet er ein Softwareentwicklungsteam, mit dem er bereits mehrere Chatbots implementiert hat. Dr. Sara D’Onofrio arbeitete als Innovation-Managerin bei der Schweizerischen Post und war bei der Chatbot-Entwicklung der IT Post mit dabei. In ihrer Dissertation beschäftigte sie sich mit der Thematik Chatbots. Prof. Dr. Edy Portmann ist Swiss Post Professor of Computer Science am Human-IST Institut der Universität Freiburg i.Üe., Schweiz, und beschäftigt sich mit Fragen rund um Informationssysteme, -verarbeitung und -beschaffung. Table of ContentsGrundlagen zu Chatbots.- Chatbots bei der Schweizerischen Post.- Erfahrungsberichte.

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