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2Statistical parametric speech synthesis
H. Zen, K. Tokuda, und A. Black. Speech Communication, 51 (11): 1039-1064 (2009)
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Speech
synthesis
Speechsynthesis
(0)
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2Performance evaluation of the speaker-independent HMM-based speech synthesis system “HTS 2007” for the Blizzard Challenge 2007
J. Yamagishi, T. Nose, H. Zen, T. Toda, und K. Tokuda. Proceedings of the 2008 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seite 3957-3960. Las Vegas, NV, USA, (März 2008)
vor 4 Jahren von @m-toman
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2007;HTS-2007;feature-space
Challenge
Challenge;HMM;HTS;speaker
HMM-based
Markov
adaptation;speaker-dependent
adaptation;speech
adaptive
analysis;Speech
analysis;hidden
approaches;speaker-independent
covariance
data;Blizzard
evaluation;speaker
matrix;Hidden
measurements;Context
modeling;Covariance
modeling;mixed-gender
modeling;performance
models;High
models;speech
speech
superconductors;Loudspeakers;Robustness;Speech
synthesis
synthesis;Blizzard
synthesis;Training
system;Acoustic
temperature
training;full-covariance
2007;HTS-2007;feature-spaceChallengeChallenge;HMM;HTS;speakerHMM-basedMarkovadaptation;speaker-dependentadaptation;speechadaptiveanalysis;Speechanalysis;hiddenapproaches;speaker-independentcovariancedata;Blizzardevaluation;speakermatrix;Hiddenmeasurements;Contextmodeling;Covariancemodeling;mixed-gendermodeling;performancemodels;Highmodels;speechspeechsuperconductors;Loudspeakers;Robustness;Speechsynthesissynthesis;Blizzardsynthesis;Trainingsystem;Acoustictemperaturetraining;full-covariance
(0)
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2Robust Speaker-Adaptive HMM-Based Text-to-Speech Synthesis
J. Yamagishi, T. Nose, H. Zen, Z. Ling, T. Toda, K. Tokuda, S. King, und S. Renals. IEEE Transactions on Audio, Speech, and Language Processing, 17 (6): 1208-1230 (August 2009)
vor 4 Jahren von @m-toman
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(artificial
HTS;HMM-based
Markov
Speech
Synthesis
System,
adaptation;speech
analysis;Speech
analysis;full-covariance
approach;text-to-speech
conversion
hidden
intelligence);speech
model;speaker-dependent
modeling;mixed-gender
modeling;robust
models;High
models;learning
reactor;Councils;Hidden
science;Continuous-stirred
science;Nose;Robustness;Speech
speaker-adaptive
speech
superconductors;Information
synthesis;Average
synthesis;Computer
synthesis;speaker
synthesis;text
synthesis;voice
tank
temperature
voice;HMM
(artificialHTS;HMM-basedMarkovSpeechSynthesisSystem,adaptation;speechanalysis;Speechanalysis;full-covarianceapproach;text-to-speechconversionhiddenintelligence);speechmodel;speaker-dependentmodeling;mixed-gendermodeling;robustmodels;Highmodels;learningreactor;Councils;Hiddenscience;Continuous-stirredscience;Nose;Robustness;Speechspeaker-adaptivespeechsuperconductors;Informationsynthesis;Averagesynthesis;Computersynthesis;speakersynthesis;textsynthesis;voicetanktemperaturevoice;HMM
(0)
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1Analysis of Speaker Adaptation Algorithms for HMM-Based Speech Synthesis and a Constrained SMAPLR Adaptation Algorithm
J. Yamagishi, T. Kobayashi, Y. Nakano, K. Ogata, und J. Isogai. IEEE Transactions on Audio, Speech, and Language Processing, 17 (1): 66-83 (Januar 2009)
vor 4 Jahren von @m-toman
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(HMM)-based
Adaptation
Markov
a
adaptation
adaptation,speaker
algorithms,regression
algorithms,speaker-dependent
analysis,Average
analysis,Speech
analysis,speaker
and
construction,regression
conversion
criteria,gender-independent
data,Vectors,constrained
design
estimation,Speech
functions,voice
likelihood
linear,estimation
matrix,Hidden
maximum
model
model,Algorithm
models,Linear
models,hidden
models,transform
posteriori
regression,Maximum
speech
structural
synthesis,Training
synthesis,model
voice,Covariance
(HMM)-basedAdaptationMarkovaadaptationadaptation,speakeralgorithms,regressionalgorithms,speaker-dependentanalysis,Averageanalysis,Speechanalysis,speakerandconstruction,regressionconversioncriteria,gender-independentdata,Vectors,constraineddesignestimation,Speechfunctions,voicelikelihoodlinear,estimationmatrix,Hiddenmaximummodelmodel,Algorithmmodels,Linearmodels,hiddenmodels,transformposterioriregression,Maximumspeechstructuralsynthesis,Trainingsynthesis,modelvoice,Covariance
(0)
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2Cross-Lingual Speaker Adaptation for HMM-Based Speech Synthesis
Y. Wu, S. King, und K. Tokuda. 6th International Symposium on Chinese Spoken Language Processing, Seite 1--4. IEEE, (Dezember 2008)
vor 4 Jahren von @m-toman
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Adaptation
Chinese
Markov
adaptation,one-to-one
analysis,source
based
context-dependent
data,Maximum
languages,Speech
likelihood
linear
mapping-
mappings,one-to-sequence
mappings,phone
method,phonetic-and-prosodic-
model,Context
model,speech
model,triphone
modeling,English,HMM-based
models
models,Loudspeakers,Mandarin
models,regression
processing,target
recognition,Speech
recognition,cross-lingual
regression,Natural
speaker
speech
synthesis,Hidden
synthesis,Stress,Target
voice
AdaptationChineseMarkovadaptation,one-to-oneanalysis,sourcebasedcontext-dependentdata,Maximumlanguages,Speechlikelihoodlinearmapping-mappings,one-to-sequencemappings,phonemethod,phonetic-and-prosodic-model,Contextmodel,speechmodel,triphonemodeling,English,HMM-basedmodelsmodels,Loudspeakers,Mandarinmodels,regressionprocessing,targetrecognition,Speechrecognition,cross-lingualregression,Naturalspeakerspeechsynthesis,Hiddensynthesis,Stress,Targetvoice
(0)
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4Large vocabulary continuous speech recognition using HTK
P. Woodland, J. Odell, V. Valtchev, und S. Young. Proceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2, Seite 125-128. Adelaide, Australia, (April 1994)
vor 4 Jahren von @m-toman
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Group;HTK;bigram
Journal
Markov
Speech
Street
University
Wall
analysis;Hidden
based
clustering;error
data;Vocabulary
decision
decoder;speech
density
dependent
dynamic
gender
hidden
independent
language
languages;software
modelling;Buildings;Decision
models;Software
models;continuous
models;mixture
models;natural
models;word-internal
network
pass
rate;gender
recognition
recognition;System
recognition;cross-word
recognition;vocabulary;ARPA
software
speech
state
systems;trigram
task;Cambridge
testing;Training
theory;decoding;hidden
tied-state
toolkit;single
tools;Speech
tools;speech
tree
trees;Decoding;Error
triphones;decision
triphones;portable
Group;HTK;bigramJournalMarkovSpeechStreetUniversityWallanalysis;Hiddenbasedclustering;errordata;Vocabularydecisiondecoder;speechdensitydependentdynamicgenderhiddenindependentlanguagelanguages;softwaremodelling;Buildings;Decisionmodels;Softwaremodels;continuousmodels;mixturemodels;naturalmodels;word-internalnetworkpassrate;genderrecognitionrecognition;Systemrecognition;cross-wordrecognition;vocabulary;ARPAsoftwarespeechstatesystems;trigramtask;Cambridgetesting;Trainingtheory;decoding;hiddentied-statetoolkit;singletools;Speechtools;speechtreetrees;Decoding;Errortriphones;decisiontriphones;portable
(0)
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2Speaker similarity evaluation of foreign-accented speech synthesis using HMM-based speaker adaptation
M. Wester, und R. Karhila. Proceedings of the 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seite 5372-5375. Prague, Czech Republic, (Mai 2011)
vor 4 Jahren von @m-toman
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Adaptation
English;Finnish-accented
English;HMM-based
Evaluation;Speaker
Markov
adaptation;average
discrimination
evaluation;synthetic
experiment;speaker
hidden
languages;Speech;Speech
model;foreign-accented
models;Data
models;Europe;Hidden
models;Natural
models;speech
similarity
speaker
speech
speech;speaker
stimuli;Adaptation
synthesis;American-accented
synthesis;HMM-synthesis;Similarity
synthesis;natural
voice
AdaptationEnglish;Finnish-accentedEnglish;HMM-basedEvaluation;SpeakerMarkovadaptation;averagediscriminationevaluation;syntheticexperiment;speakerhiddenlanguages;Speech;Speechmodel;foreign-accentedmodels;Datamodels;Europe;Hiddenmodels;Naturalmodels;speechsimilarityspeakerspeechspeech;speakerstimuli;Adaptationsynthesis;American-accentedsynthesis;HMM-synthesis;Similaritysynthesis;naturalvoice
(0)
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2Synthesizing visual speech trajectory with minimum generation error
L. Wang, Y. Wu, X. Zhuang, und F. Soong. Proceedings of the 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seite 4580-4583. Prague, Czech Republic, (Mai 2011)
vor 4 Jahren von @m-toman
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HMM;heuristic
Markov
algorithm;traditional
alignment;probabilistic
descent
error
error;photo-real;talking
estimation;visual
generation
head;trajectory-guided;visual
hidden
likelihood
maximum
method;mean
method;optimal
methods;speech
models;Speech;Speech
models;mean
reduction;minimum
speech
square
state
synthesis
synthesis;Acoustics;Hidden
synthesis;Training;Trajectory;Visualization;minimum
synthesis;audiovisual
training
trajectory
HMM;heuristicMarkovalgorithm;traditionalalignment;probabilisticdescenterrorerror;photo-real;talkingestimation;visualgenerationhead;trajectory-guided;visualhiddenlikelihoodmaximummethod;meanmethod;optimalmethods;speechmodels;Speech;Speechmodels;meanreduction;minimumspeechsquarestatesynthesissynthesis;Acoustics;Hiddensynthesis;Training;Trajectory;Visualization;minimumsynthesis;audiovisualtrainingtrajectory
(0)
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1Unsupervised and phonologically controlled interpolation of Austrian German language varieties for speech synthesis
M. Toman, M. Pucher, S. Moosmüller, und D. Schabus. Speech Communication, (2015)
vor 4 Jahren von @m-toman
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HMM-based
speech
synthesis
HMM-basedspeechsynthesis
(0)
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2Speech parameter generation algorithms for HMM-based speech synthesis
K. Tokuda, T. Yoshimura, T. Masuko, T. Kobayashi, und T. Kitamura. Proceedings of the 2000 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3, Seite 1315-1318. Istanbul, Turkey, (Juni 2000)
vor 4 Jahren von @m-toman
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HMM-based
HMM;observation
Markov
algorithm;multi-mixture
algorithms;speech
estimation;speech
feature
generation
likelihood
models;maximum
parameter
sequence;hidden
sequence;state
speech
structure;forward-backward
synthesis;
synthesis;dynamic
vector;formant
vector;spectral
vector;speech
HMM-basedHMM;observationMarkovalgorithm;multi-mixturealgorithms;speechestimation;speechfeaturegenerationlikelihoodmodels;maximumparametersequence;hiddensequence;statespeechstructure;forward-backwardsynthesis;synthesis;dynamicvector;formantvector;spectralvector;speech
(0)
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2Speech Synthesis Based on Hidden Markov Models
K. Tokuda, Y. Nankaku, T. Toda, H. Zen, J. Yamagishi, und K. Oura. Proceedings of the IEEE, 101 (5): 1234-1252 (April 2013)
vor 4 Jahren von @m-toman
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(HMM);statistical
(TTS)
Markov
approach;Hidden
hidden
learning;Text
model
model;speech
models;Information
models;speech
parametric
processing;HMM-based
processing;Parametric
processing;Speech
speech
statistics;Speech
synthesis
synthesis;Statistical
synthesis;hidden
synthesis;text-to-speech
synthesis;unit-selection
system;Hidden
(HMM);statistical(TTS)Markovapproach;Hiddenhiddenlearning;Textmodelmodel;speechmodels;Informationmodels;speechparametricprocessing;HMM-basedprocessing;Parametricprocessing;Speechspeechstatistics;Speechsynthesissynthesis;Statisticalsynthesis;hiddensynthesis;text-to-speechsynthesis;unit-selectionsystem;Hidden
(0)
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1Realistic Visual Speech Synthesis Based on Hybrid Concatenation Method
J. Tao, L. Xin, und P. Yin. IEEE Transactions on Audio, Speech, and Language Processing, 17 (3): 469-477 (März 2009)
vor 4 Jahren von @m-toman
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(HMM);inversion;speech-driven
Gaussian
HMM;hybrid
Markov
Viterbi
algorithm;Fused
animation;Hidden
animation;frame
animation;unit
applications;two-layer
concatenation
concatenation;visual
facial
hidden
level-based
media;Viterbi
method;fused
method;real-time
method;visual
methods;Speech
mixture
model
model;facial
models;Hybrid
models;search
power
problems;speech
processes;emotion
recognition;hidden
search
selection
speech
synthesis
synthesis;Acceleration;Facial
synthesis;Gaussian
synthesis;Stability;Streaming
systems;Real
systems;Search
time
unit
(HMM);inversion;speech-drivenGaussianHMM;hybridMarkovViterbialgorithm;Fusedanimation;Hiddenanimation;frameanimation;unitapplications;two-layerconcatenationconcatenation;visualfacialhiddenlevel-basedmedia;Viterbimethod;fusedmethod;real-timemethod;visualmethods;Speechmixturemodelmodel;facialmodels;Hybridmodels;searchpowerproblems;speechprocesses;emotionrecognition;hiddensearchselectionspeechsynthesissynthesis;Acceleration;Facialsynthesis;Gaussiansynthesis;Stability;Streamingsystems;Realsystems;Searchtimeunit
(0)
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1A Style Adaptation Technique for Speech Synthesis Using HSMM and Suprasegmental Features
M. Tachibana, J. Yamagishi, T. Masuko, und T. Kobayashi. IEICE Transactions on Information and Systems, E89-D (3): 1092-1099 (März 2006)
vor 4 Jahren von @m-toman
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(HSMM),
(MLLR)
HMM-based
adaptation,
emotional
expression,
hidden
likelihood
linear
maximum
model
regression
semi-Markov
speaking
speech
style
style,
synthesis,
(HSMM),(MLLR)HMM-basedadaptation,emotionalexpression,hiddenlikelihoodlinearmaximummodelregressionsemi-Markovspeakingspeechstylestyle,synthesis,
(0)
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1Joint Audiovisual Hidden Semi-Markov Model-based Speech Synthesis
D. Schabus, M. Pucher, und G. Hofer. IEEE Journal of Selected Topics in Signal Processing, 8 (2): 336-347 (April 2014)
vor 4 Jahren von @m-toman
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Acoustics;Hidden
Markov
animation;hidden
head
model;speech
models;Joints;Speech;Synchronization;Training;Visualization;Audiovisual
speech
synthesis;HMM-based
synthesis;facial
synthesis;talking
Acoustics;HiddenMarkovanimation;hiddenheadmodel;speechmodels;Joints;Speech;Synchronization;Training;Visualization;Audiovisualspeechsynthesis;HMM-basedsynthesis;facialsynthesis;talking
(0)
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2Design and development of spoken dialog systems incorporating speech synthesis of Viennese varieties
M. Pucher, F. Neubarth, und D. Schabus. Proceedings of the 12th international conference on Computers helping people with special needs (ICCHP), Seite 361-366. Vienna, Austria, (Juli 2010)
vor 4 Jahren von @m-toman
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dialect,
dialog
speech
spoken
synthesis,
system
dialect,dialogspeechspokensynthesis,system
(0)
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1Analysis of unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis using KLD-based transform mapping
K. Oura, J. Yamagishi, M. Wester, S. King, und K. Tokuda. Speech Communication, 54 (6): 703-714 (Juli 2012)
vor 4 Jahren von @m-toman
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adaptation
adaptation,hmm-based
cross-lingual
speaker
speech
synthesis,speech-to-speech
translation,unsupervised
adaptationadaptation,hmm-basedcross-lingualspeakerspeechsynthesis,speech-to-speechtranslation,unsupervised
(0)
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1Emphatic Visual Speech Synthesis
J. Melenchón, E. Martínez, F. De La Torre, und J. Montero. IEEE Transactions on Audio, Speech, and Language Processing, 17 (3): 459-468 (März 2009)
vor 4 Jahren von @m-toman
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behavioral
emphatic
facial
framework;photometry;statistical
interaction;face
interpolation;person-specific
recognition;interpolation;speech
speech
synthesis
synthesis;
synthesis;geodesic
visual
behavioralemphaticfacialframework;photometry;statisticalinteraction;faceinterpolation;person-specificrecognition;interpolation;speechspeechsynthesissynthesis;synthesis;geodesicvisual
(0)
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2Text-to-visual speech synthesis based on parameter generation from HMM
T. Masuko, T. Kobayashi, M. Tamura, J. Masubuchi, und K. Tokuda. Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 6, Seite 3745-3748. Seattle, WA, USA, (Mai 1998)
vor 4 Jahren von @m-toman
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2D
HMM;syllable
HMM;synchronized
Markov
algorithm;phonetic
animation;ML;coarticulation;dynamic
animation;feature
contour
extraction;hidden
features;generated
generation
lip
models;speech
motion;text-to-visual
mouth
movements;parameter
movements;synthesis
parameter
phase;synthetic
phase;visual
sequences;computer
shapes;input
speech
synthesis;synchronisation;
synthesis;training
text;lip
transcription;sentence
2DHMM;syllableHMM;synchronizedMarkovalgorithm;phoneticanimation;ML;coarticulation;dynamicanimation;featurecontourextraction;hiddenfeatures;generatedgenerationlipmodels;speechmotion;text-to-visualmouthmovements;parametermovements;synthesisparameterphase;syntheticphase;visualsequences;computershapes;inputspeechsynthesis;synchronisation;synthesis;trainingtext;liptranscription;sentence
(0)
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1Accurate visible speech synthesis based on concatenating variable length motion capture data
J. Ma, R. Cole, B. Pellom, W. Ward, und B. Wise. IEEE Transactions on Visualization and Computer Graphics, 12 (2): 266-276 (2006)
vor 4 Jahren von @m-toman
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(artificial
Automated;Reproducibility
Biological;Movement;Pattern
Computer-Assisted;Imaging,
Enhancement;Image
Graphics;Computer
Intelligence;Computer
Interface;Video
Interpretation,
Measurement;User-Computer
Production
Recognition,
Recording
Results;Sensitivity
Retrieval;Models,
Simulation;Face;Image
Specificity;Speech;Speech
Storage
Three-Dimensional;Information
algorithm;speech
analysis;Speech
analysis;learning
and
animation
animation;Humans;Large-scale
animation;character
animation;coarticulation
animation;face
capture
codes;Facial
computer
data;optimal
effect;facial
effect;virtual
face
human.;visible
intelligence);search
learning
learning;Prototypes;Speech
model;coarticulation
modelling;speech
motion
motion;lip
motion;machine
of
problems;solid
processing;Speech
prototype;Concatenated
recognition;image
sequence;search
speech
speech;Algorithms;Artificial
speech;visual
synthesis;3D
synthesis;Face
synthesis;visual
system;visible
systems;Lips;Machine
technique;motion
(artificialAutomated;ReproducibilityBiological;Movement;PatternComputer-Assisted;Imaging,Enhancement;ImageGraphics;ComputerIntelligence;ComputerInterface;VideoInterpretation,Measurement;User-ComputerProductionRecognition,RecordingResults;SensitivityRetrieval;Models,Simulation;Face;ImageSpecificity;Speech;SpeechStorageThree-Dimensional;Informationalgorithm;speechanalysis;Speechanalysis;learningandanimationanimation;Humans;Large-scaleanimation;characteranimation;coarticulationanimation;facecapturecodes;Facialcomputerdata;optimaleffect;facialeffect;virtualfacehuman.;visibleintelligence);searchlearninglearning;Prototypes;Speechmodel;coarticulationmodelling;speechmotionmotion;lipmotion;machineofproblems;solidprocessing;Speechprototype;Concatenatedrecognition;imagesequence;searchspeechspeech;Algorithms;Artificialspeech;visualsynthesis;3Dsynthesis;Facesynthesis;visualsystem;visiblesystems;Lips;Machinetechnique;motion
(0)
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2HMM-Based Hierarchical Unit Selection Combining Kullback-Leibler Divergence with Likelihood Criterion
Z. Ling, und R. Wang. Proceedings of the 2007 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4, Seite 1245-1248. Honolulu, HI, USA, (April 2007)
vor 4 Jahren von @m-toman
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Markov
Synthesis
criterion;Context
criterion;frame
criterion;maximum
criterion;phone
divergence;concatenative
estimation;speech
function
function;Databases;Diversity
hidden
hierarchical
level
likelihood
model;likelihood
modeling;Cost
models;Signal
models;maximum
programming;Flowcharts;Hidden
reception;Dynamic
segments;hidden
selection;Kullback-Leibler
sized
speech
synthesis
synthesis;HMM-based
synthesis;Speech
synthesis;Synthesizers;HMM;KLD;Speech
system;cost
unit
units;frame
units;statistical
MarkovSynthesiscriterion;Contextcriterion;framecriterion;maximumcriterion;phonedivergence;concatenativeestimation;speechfunctionfunction;Databases;Diversityhiddenhierarchicallevellikelihoodmodel;likelihoodmodeling;Costmodels;Signalmodels;maximumprogramming;Flowcharts;Hiddenreception;Dynamicsegments;hiddenselection;Kullback-Leiblersizedspeechsynthesissynthesis;HMM-basedsynthesis;Speechsynthesis;Synthesizers;HMM;KLD;Speechsystem;costunitunits;frameunits;statistical
(0)
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1A frequency warping approach to speaker normalization
L. Lee, und R. Rose. IEEE Transactions on Speech and Audio Processing, 6 (1): 49--60 (1998)
vor 4 Jahren von @m-toman
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Cepstral
Markov
analysis,Cepstrum,Degradation,Error
analysis,Filter
analysis,speaker
bank,Frequency
based
cepstrum
complexity
connected
digit
error
estimation,Maximum
estimation,Shape,Speech
estimation,low
factor
feature
filters,continuous
frequency
likelihood
model,hidden
models,linear
normalization,speech
performance,telephone
processing,speech
rate
recognition
recognition,Telephony,band-pass
recognition,experiment,filterbank,filtering
recognition,very
reduction
shape,word
short
speech
theory,hidden
tract
utterances,vocal
warping
warping,maximum
warping,mel-frequency
CepstralMarkovanalysis,Cepstrum,Degradation,Erroranalysis,Filteranalysis,speakerbank,Frequencybasedcepstrumcomplexityconnecteddigiterrorestimation,Maximumestimation,Shape,Speechestimation,lowfactorfeaturefilters,continuousfrequencylikelihoodmodel,hiddenmodels,linearnormalization,speechperformance,telephoneprocessing,speechraterecognitionrecognition,Telephony,band-passrecognition,experiment,filterbank,filteringrecognition,veryreductionshape,wordshortspeechtheory,hiddentractutterances,vocalwarpingwarping,maximumwarping,mel-frequency
(0)
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1Restructuring speech representations using a pitch-adaptive time–frequency smoothing and an instantaneous-frequency-based F0 extraction: Possible role of a repetitive structure in sounds
H. Kawahara, I. Masuda-Katsuse, und A. de Cheveigné. Speech Communication, 27 (3–4): 187-207 (1999)
vor 4 Jahren von @m-toman
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Speech
analysis
Speechanalysis
(0)
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3Design of a linguistic statistical decoder for the recognition of continuous speech
F. Jelinek, L. Bahl, und R. Mercer. IEEE Transactions on Information Theory, 21 (3): 250-256 (Mai 1975)
vor 4 Jahren von @m-toman
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Decoding;Speech
control;Automatic
intelligence;Automatic
languages;Speech
recognition;Artificial
recognition;Character
recognition;Decoding;Dictionaries;Loudspeakers;Natural
recognition;Vocabulary
speech
Decoding;Speechcontrol;Automaticintelligence;Automaticlanguages;Speechrecognition;Artificialrecognition;Characterrecognition;Decoding;Dictionaries;Loudspeakers;Naturalrecognition;Vocabularyspeech
(0)
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3Unit selection in a concatenative speech synthesis system using a large speech database
A. Hunt, und A. Black. Proceedings of the 1996 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1, Seite 373-376. Atlanta, GA, USA, (Mai 1996)
vor 4 Jahren von @m-toman
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Viterbi
algorithm
context
cost;state
cost;waveform
database;natural
database;training;transition
decoding;concatenative
decoding;search
estimation;Viterbi
information;prosodic
information;pruned
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1Learning optimal audiovisual phasing for a HMM-based control model for facial animation
O. Govokhina, G. Bailly, und G. Breton. Proceedings of the 6th ISCA Workshop on Speech Synthesis (SSW), Seite 1-4. Bonn, Germany, (22.08.2007)
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system;
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2Trainable videorealistic speech animation
T. Ezzat, G. Geiger, und T. Poggio. Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), Seite 388-398. San Antonio, TX, USA, (Juli 2002)
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animation,
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1Speaker adaptation using constrained estimation of Gaussian mixtures
V. Digalakis, D. Rtischev, und L. Neumeyer. IEEE Transactions on Speech and Audio Processing, 3 (5): 357-366 (September 1995)
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1Audiovisual speech processing
T. Chen. IEEE Signal Processing Magazine, 18 (1): 9-21 (Januar 2001)
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3Automatic segmentation and labeling of speech based on Hidden Markov Models
F. Brugnara, D. Falavigna, und M. Omologo. Speech Communication, 12 (4): 357-370 (August 1993)
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2Italian Speakers Learn Lexical Stress of German Morphologically Complex Words
M. Bissiri, und H. Pfitzinger. Speech Commununication, 51 (10): 933--947 (Oktober 2009)
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AssistedCALL,ComputerIntensity,Intonation,LanguageLearning,LexicalLocalPerformanceProsodyassessment,modificationrate,speechstress,
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2The DRAGON system--An overview
J. Baker. IEEE Transactions on Acoustics, Speech and Signal Processing, 23 (1): 24-29 (Februar 1975)
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1Evaluation of movement generation systems using the point-light technique
G. Bailly, G. Gibert, und M. Odisio. Proceedings of the 2002 IEEE Workshop on Speech Synthesis, Seite 27-30. Santa Monica, CA, USA, (September 2002)
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2Statistical parametric speech synthesis

2Performance evaluation of the speaker-independent HMM-based speech synthesis system “HTS 2007” for the Blizzard Challenge 2007

2Robust Speaker-Adaptive HMM-Based Text-to-Speech Synthesis

1Analysis of Speaker Adaptation Algorithms for HMM-Based Speech Synthesis and a Constrained SMAPLR Adaptation Algorithm

2Cross-Lingual Speaker Adaptation for HMM-Based Speech Synthesis

4Large vocabulary continuous speech recognition using HTK

2Speaker similarity evaluation of foreign-accented speech synthesis using HMM-based speaker adaptation

2Synthesizing visual speech trajectory with minimum generation error

1Unsupervised and phonologically controlled interpolation of Austrian German language varieties for speech synthesis

2Speech parameter generation algorithms for HMM-based speech synthesis

2Speech Synthesis Based on Hidden Markov Models

1Realistic Visual Speech Synthesis Based on Hybrid Concatenation Method

1A Style Adaptation Technique for Speech Synthesis Using HSMM and Suprasegmental Features

1Joint Audiovisual Hidden Semi-Markov Model-based Speech Synthesis

2Design and development of spoken dialog systems incorporating speech synthesis of Viennese varieties

1Analysis of unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis using KLD-based transform mapping

1Emphatic Visual Speech Synthesis

2Text-to-visual speech synthesis based on parameter generation from HMM

1Accurate visible speech synthesis based on concatenating variable length motion capture data

2HMM-Based Hierarchical Unit Selection Combining Kullback-Leibler Divergence with Likelihood Criterion

1A frequency warping approach to speaker normalization

1Restructuring speech representations using a pitch-adaptive time–frequency smoothing and an instantaneous-frequency-based F0 extraction: Possible role of a repetitive structure in sounds

3Design of a linguistic statistical decoder for the recognition of continuous speech

3Unit selection in a concatenative speech synthesis system using a large speech database

1Learning optimal audiovisual phasing for a HMM-based control model for facial animation

2Trainable videorealistic speech animation

1Speaker adaptation using constrained estimation of Gaussian mixtures

1Audiovisual speech processing

3Automatic segmentation and labeling of speech based on Hidden Markov Models

2Italian Speakers Learn Lexical Stress of German Morphologically Complex Words

2The DRAGON system--An overview

1Evaluation of movement generation systems using the point-light technique

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