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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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Robust Automatic Speech Recognition

Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech;

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Digital Speech Processing

A study of digital speech processing, synthesis and recognition. This second edition contains new sections on the international;

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Noise Reduction Based on Microphone Array and Post-Filtering

. The book describes the theory, implementation and applications of multi-channel noise reduction for robust hands-free speech recognition;

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Robust Adaptation to Non-Native Accents in Automatic Speech Recognition

Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness;

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Speech Processing in Mobile Environments

in the book exploit the speech events which are robust in noisy environments. Accurate estimation of these crucial events will be useful for;

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Speech Processing in the Auditory System

to understand speech in uncertain, potentially adverse acoustic environments, currently the bane of both hearing aid and speech recognition;

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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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Soft Computing Implementation of Automatic Speech Recognition

This work assimilates an introduction to the Human speech production system, Fundamentals of speech recognition, the methods for data;

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Cognitive Models of Speech Processing

Presents extensive reviews of current thinking on psycholinguistic and computational topics in speech recognition and natural language;

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Spectral Analysis of Signals

comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate;

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Self-Learning Speaker Identification

Current speech recognition systems are based on speaker independent speech models and suffer from inter-speaker variations in speech signal;

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Supervised Sequence Labelling with Recurrent Neural Networks

raw audio or video. Experimental validation is provided by state-of-the-art results in speech and handwriting recognition.;

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Speech Recognizer Adaptation

This book focuses on the adaptation of speech recognizers to noisy or reverberant environment. Therefore, three corpora in different noise;

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Speech Processing and Soft Computing

enhancement and speech recognition in order to provide robust systems. The material is especially useful to graduate students and experienced;

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Cognitive Models of Speech Processing

recognition and natural-language processing, along with a substantial body of new experimental data and computational simulations. Topics range from;

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Uncertain Models and Robust Control

Uncertain Models and Robust Control .;

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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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Pattern Recognition And Big Data

, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data;

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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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Semiparametric Theory and Missing Data

methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and;

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Query Processing over Uncertain Databases

Due to measurement errors, transmission lost, or injected noise for privacy protection, uncertainty exists in the data of many real;

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Robust Representation for Data Analytics

for Data Analytics covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition;

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Speech Recognition in Adverse Conditions

Speech recognition in 'adverse conditions' has been a familiar area of research in computer science, engineering, and hearing sciences for;

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Pattern Recognition in Speech and Language Processing

speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have;

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Discrete-Time Processing of Speech Signals

speech coding for communications systems to biomedical applications of speech analysis and recognition. Ideal for self--study or as a course;

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Speech Recognition Based on Voip Coding

scene, automatic speech recognition is a promising way for an easy and natural user access to network services. However, mobile devices are;

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