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Robust Emotion Recognition using Spectral and Prosodic Features

improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.;

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Handling Emotions in Human-Computer Dialogues

. With the robust recognition of emotions from speech signals as their goal, the authors analyze the effectiveness of using a plain emotion;

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Multilingual Phone Recognition in Indian Languages

improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem;

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Human Emotion Recognition from Face Images

using them individually. There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and;

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Human Emotion Recognition from Face Images

using them individually. There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and;

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Speech Processing in Mobile Environments

provide insights into designing and developing robust methods to process the speech in mobile environments. Covering temporal and spectral;

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Speech Acts & Prosodic Modeling in Service-Oriented Dialog Systems

to special applications such as emotion recognition, and/or special user groups, such as children or handicapped users, are not included;

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Towards Adaptive Spoken Dialog Systems

negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions;

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Robust Speaker Recognition in Noisy Environments

for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse;

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Robust Parallel Speech Recognition

form a single recognition result. As shown on different data sets the parallel speech recognition system is much more robust to noise and;

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Speech Recognition and Processing

Finland. Topics like speech recognition, noise cancellation, speech enhancement and emotion recognition have been described in this book;

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Real-Time Automatic Emotion Recognition from Speech

. Therefore, this book investigates real-time automatic emotion recognition from acoustic features of speech in several experiments for suitable audio;

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Introduction to EEG- and Speech-Based Emotion Recognition

Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using;

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A Pattern Recognition Approach to Electromyography Data

standard deviation) for EMG signal recognition and using them along with several popular features (area under the curve, wavelength function;

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Efficient trademark retrieval using weighted image features

required information from these databases. Fast retrieval and robustness are two main criteria for efficient recognition of an object using image;

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Gesture Recognition

In the opening chapter of Gesture Recognition: Performance, Applications and Features, the authors discuss gesture recognition and its role;

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Emotion Recognition

A timely book containing foundations and current research directions on emotion recognition by facial expression, voice, gesture and;

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Robust Adaptation to Non-Native Accents in Automatic Speech Recognition

features. Furthermore, a specific pronunciation modelling technique that allows the automatic derivation of non-native pronunciations without using;

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Systems of Prosodic and Paralinguistic Features in English

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Extraction of Prosody for Automatic Speaker Language Emotion and Speech Recogn

information on the significance of prosody for emotion recognition and various prosody-based approaches for automatic emotion recognition from speech.;

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Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems

recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the;

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Affective Computing and Intelligent Interaction

, affective text and dialogue processing, recognizing affect using physiological measures, computational models of emotion and theoretical foundations;

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Robust Automatic Speech Recognition

recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation;

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Logo Recognition

robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy;

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Logo Recognition

robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy;

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Accurate and Robust Spectral Testing with Relaxed Instrumentation Requirements

This book introduces a family of new methods for accurate and robust spectral testing and fills an information gap, as the requirements;

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Music Emotion Recognition

Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains;

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