Speech and Computer
Andrey Ronzhin
Sold by buchversandmimpf2000, Emtmannsberg, BAYE, Germany
AbeBooks Seller since January 23, 2017
New - Soft cover
Condition: New
Ships from Germany to U.S.A.
Quantity: 1 available
Add to basketSold by buchversandmimpf2000, Emtmannsberg, BAYE, Germany
AbeBooks Seller since January 23, 2017
Condition: New
Quantity: 1 available
Add to basketThis item is printed on demand - Print on Demand Titel. Neuware -Automatic Speech Recognition based on Neural Networks.- Machine Processing of Dialogue States; Speculations on Conversational Entropy.- Speech Recognition Challenges in the Car Navigation Industry.- A Comparison of Acoustic Features of Speech of Typically Developing Children and Children with Autism Spectrum Disorders.- A Deep Neural Networks (DNN) Based models for a Computer Aided Pronunciation Learning System.- A Linguistic Interpretation of the Atom Decomposition of Fundamental Frequency Contour for American English.- A Phonetic Segmentation Procedure Based on Hidden Markov Models.- A Preliminary Exploration of Group Social Engagement Level Recognition in Multiparty Casual Conversation.- An Agonist-Antagonist Pitch Production Model.- An Algorithm for Phase Manipulation in a Speech Signal.- An Exploratory Study on Sociolinguistic Variation of Russian Everyday Speech.- Adaptation of DNN Acoustic Models using KL-divergence Regularization and Multi-Task Training.- Advances in STC Russian Spontaneous Speech Recognition System.- Approaches for Out-of-Domain Adaptation to Improve Speaker Recognition Performance.- Assessment of the Relation Between Low-Frequency Features and Velum Opening by Using Real Articulatory Data.- Automatic Summarization of Highly Spontaneous Speech.- Backchanneling via Twitter Data for Conversational Dialogue Systems.- Bio-Inspired Sparse Representation of Speech and Audio Using Psychoacoustic Adaptive Matching Pursuit.- Combining Atom Decomposition of the F0 Track and HMM-based Phonological Phrase Modelling for Robust Stress Detection in Speech.- Comparative analysis of classifiers for automatic language recognition in spontaneous speech.- Comparison of Retrieval Approaches and Blind Relevance Feedback Methods within the Czech Speech Information Retrieval.- Convolutional Neural Network in the Task of Speaker Change Detection.- Design of a Speech Corpus for Research on Cross-Lingual Prosody Transfer.- Designing High-Coverage Multi-Level TextCorpus for Non-Professional-Voice Conservation.- Designing Syllable Models for an HMM based Speech Recognition System.- Detecting Filled Pauses and Lengthenings in Russian Spontaneous Speech using SVM.- Detecting Laughter and Filler Events by Time Series Smoothing with Genetic Algorithms.- Detecting State of Aggression in Sentences using CNN.- DNN-based Acoustic Modeling for Russian Speech Recognition Using Kaldi.- DNN-Based Duration Modeling for Synthesizing Short Sentences.- Emotional Speech of 3-Years Old Children: Norm-Risk-Deprivation.- Ensemble Deep Neural Network based Waveform-Driven Stress Model for Speech Synthesis.- Evaluation of Response Times on a Touch Screen using Stereo Panned Speech Command Auditory Feedback.- Evaluation of the Speech Quality During Rehabilitation after Surgical Treatment of the Cancer of Oral Cavity and Oropharynx based on a Comparison of the Fourier Spectra.- Experiments with One-Class Classifier as a Predictor of Spectral Discontinuities in Unit Concatenation.- Exploring GMM-derived Features for Unsupervised Adaptation of Deep Neural Network Acoustic Models.- Feature Space VTS with Phase Term Modeling.- Finding Speaker Position Under Difficult Acoustic Conditions.- Fusing Various Audio Feature Sets for Detection of Parkinson's Disease from Sustained Voice and Speech Recordings.- HAVRUS Corpus: High-speed Recordings of Audio-Visual Russian Speech.- Human-Smartphone Interaction for Dangerous Situation Detection & Recommendation Generation while Driving.- Improving Automatic Speech Recognition Containing Additive Noise Using Deep Denoising Autoencoders of LSTM Networks.- Improving the Quality of Automatic Speech Recognition in Trucks.- Improving Recognition of Dysarthric Speech Using Severity Based Tempo Adaptation.- Improving Robustness of Speaker Verification by Fusion of Prompted Text-Dependent & Text-Independent Operation Modalities.- Improvements to Prosodic Variation.
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