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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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Noise Reduction Based on Microphone Array and Post-Filtering

Acoustic interfering noise signals dramatically degrade the performance of many speech applications, such as automatic 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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Robust Parallel Speech Recognition

This book focuses on automatic speech recognition in clean and noisy or reverbrant environments. Therefore, a parallel speech recognition;

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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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Soft Computing Implementation of Automatic Speech Recognition

without GA. The use of GAs for feature optimizers is a novel concept in Automatic Speech Recognition hence the system becomes more robust to noise;

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Automatic Speech Recognition: A Deep Learning Approach

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep;

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Emulating Human Speech Recognition

This book presents a systematic approach to the automatic recognition of simultaneous speech signals using computational auditory scene;

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Information Security for Automatic Speaker Identification

critical areas of automatic speech recognition. Included are topics on speech watermarking, speech encryption, steganography, multilevel security;

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Like Humans Do

This book presents a systematic approach to the automatic recognition of simultaneous speech signals using computational auditory scene;

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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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Incorporating Knowledge Sources into Statistical Speech Recognition

Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech;

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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 and Computer

of computer speech processing including audio signal processing, automatic speech recognition, speaker recognition, computational paralinguistics;

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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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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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Advances in Nonlinear Speech Processing

organized in topical sections on speech and audio analysis; speech synthesis; speech-based biomedical applications; automatic speech recognition;

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Distant Speech Recognition

A complete overview of distant automatic speech recognition The performance of conventional Automatic Speech Recognition (ASR) systems;

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Human and Automatic Speaker Recognition over Telecommunication Channels

This work addresses the evaluation of the human and the automatic speaker recognition performances under different channel distortions;

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Advances in Speech and Language Technologies for Iberian Languages

different topics: Speech Production, Analysis, Coding and Synthesis; Automatic Speech Recognition; Paralinguistic Speaker Trait;

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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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Speech Recognition

Automatic Speech Recognition (ASR) is the enabling technology for hands-free dictation and voice-triggered computer menus. It is becoming;

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Who spoke when?

. Generally we can find two main applications for speaker diarization. Automatic Speech Recognition systems make use of the speaker homogeneous;

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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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Text, Speech and Dialogue

submissions. The papers are organized in topical sections on corpora and language resources, speech recognition, tagging, classification and parsing;

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Text Speech and Dialogue

submissions. They focus on topics such as corpora and language resources; speech recognition; tagging, classification and parsing of text and speech;

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Text, Speech, and Dialogue

127 submissions. They focus on topics such as corpora and language resources; speech recognition; tagging, classification and parsing of text;

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