tag :: Speech

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Publikationen (verstecken)36
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1Demonstration of a Serious Game for Spoken Language Experiments - GDX
D. Duran, und N. Lewandowski. Workshop on Games and Natural Language Processing, Seite 68--78. Marseille, France, ACL, European Language Resources Association, (Mai 2020)
vor 4 Jahren von @n.lewandowski
alle anzeigen
experiment
game
myown
perception
speech
experimentgamemyownperceptionspeech
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2Prosodic and segmental convergence in spontaneous German conversations
N. Lewandowski, and A. Schweitzer. (Oktober 2010)
4 years ago by @n.lewandowski
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convergence
myown
speech
convergencemyownspeech
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1Perception‐production loop in native–non‐native dialogs: Phonetic convergence
N. Lewandowski, and G. Dogil. (April 2009)
4 years ago by @n.lewandowski
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convergence
myown
phonetic
speech
convergencemyownphoneticspeech
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1A 3D computer game for testing perception of acoustic detail in speech
D. Duran, N. Lewandowski, and A. Schweitzer. Proc. Mtgs. Acoust., 28 (1): 060004-- (September 2016)
4 years ago by @n.lewandowski
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attention
detail
myown
perception
phonetic
speech
attentiondetailmyownperceptionphoneticspeech
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2Individual Differences in Implicit Attention to Phonetic Detail in Speech Perception
N. Lewandowski, and D. Duran. Proc. Interspeech 2019, page 2255-2259. Interspeech 2019, (2019)
4 years ago by @n.lewandowski
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attention
convergence
myown
phonetic
speech
attentionconvergencemyownphoneticspeech
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2CoLoSS: Cognitive load corpus with speech and performance data from a symbol-digit dual-task
R. Herms, M. Wirzberger, M. Eibl, and G. Rey. Proceedings of the 11th International Language Resources and Evaluation Conference (LREC 2018), page 4312--4317. Miyazaki, Japan, European Language Resource Association (ELRA), (2018)
6 years ago by @mariawirzberger
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cognition
corpus
dual-task
learning
load
myown
performance
speech
cognitioncorpusdual-tasklearningloadmyownperformancespeech
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1Cognitive load influences performance, speech and physiological parameters in a multimodal dual-task setting
M. Wirzberger, R. Herms, S. Esmaeili Bijarsari, G. Rey, and M. Eibl. Abstracts of the 60th Conference of Experimental Psychologists, page 296. Lengerich, Pabst Science Publishers, (2018)
6 years ago by @mariawirzberger
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cognition
learning
load
myown
performance
physiology
speech
cognitionlearningloadmyownperformancephysiologyspeech
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1Influences of cognitive load on learning performance, speech and physiological parameters in a dual-task setting
M. Wirzberger, R. Herms, S. Esmaeili Bijarsari, G. Rey, and M. Eibl. Abstracts of the 20th Conference of the European Society for Cognitive Psychology, page 161. Potsdam, Germany, (2017)
6 years ago by @mariawirzberger
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cognition
dual-task
learning
load
myown
performance
physiology
speech
cognitiondual-tasklearningloadmyownperformancephysiologyspeech
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3Convergence of articulation rate in spontaneous speech.
A. Schweitzer, and N. Lewandowski. INTERSPEECH, page 525-529. ISCA, (2013)
6 years ago by @n.lewandowski
show all tags
convergence
speech
convergencespeech
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2IEMOCAP: Interactive emotional dyadic motion capture database
C. Busso, M. Bulut, C. Lee, A. Kazemzadeh, E. Mower, S. Kim, J. Chang, S. Lee, and S. Narayanan. Language resources and evaluation, 42 (4): 335--359 (2008)
8 years ago by @michaelneumann
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Databases,
English
IEMOCAP
Speech
data,
databases,
emotion
Databases,EnglishIEMOCAPSpeechdata,databases,emotion
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2Speech emotion recognition using deep neural network and extreme learning machine.
K. Han, D. Yu, and I. Tashev. Interspeech, page 223--227. (2014)
8 years ago by @michaelneumann
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DNN,
ELM,
IEMOCAP,
classification
emotion
recognition,
speech
DNN,ELM,IEMOCAP,classificationemotionrecognition,speech
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2Survey on speech emotion recognition: Features, classification schemes, and databases
M. El Ayadi, M. Kamel, and F. Karray. Pattern Recognition, 44 (3): 572--587 (2011)
8 years ago by @michaelneumann
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emotion
recognition
speech
emotionrecognitionspeech
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2Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge
B. Schuller, A. Batliner, S. Steidl, and D. Seppi. Speech Communication, 53 (9): 1062--1087 (2011)
8 years ago by @michaelneumann
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Feature
emotion
recognition,
review
selection,
speech
Featureemotionrecognition,reviewselection,speech
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1Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
G. Hinton, L. Deng, D. Yu, G. Dahl, A. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. Sainath and 1 other author(s). IEEE Signal Processing Magazine, 29 (6): 82--97 (2012)
8 years ago by @michaelneumann
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TIMIT
acoustic
deep
modeling,
networks,
neural
recognition,
speech
TIMITacousticdeepmodeling,networks,neuralrecognition,speech
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2Towards End-To-End Speech Recognition with Recurrent Neural Networks.
A. Graves, and N. Jaitly. ICML, 14, page 1764--1772. (2014)
8 years ago by @michaelneumann
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RNN
end-to-end
learning,
recognition,
speech
RNNend-to-endlearning,recognition,speech
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1Analysis of cnn-based speech recognition system using raw speech as input
D. Palaz, R. Collobert, and others. Proceedings of Interspeech, (2015)
8 years ago by @michaelneumann
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Automatic
CNN,
TIMIT
raw
recognition,
signal,
speech
AutomaticCNN,TIMITrawrecognition,signal,speech
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2Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition
O. Abdel-Hamid, A. Mohamed, H. Jiang, and G. Penn. 2012 IEEE international conference on Acoustics, speech and signal processing (ICASSP), page 4277--4280. IEEE, (2012)
8 years ago by @michaelneumann
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CNN,
NN-HMM
hybrid
recognition;
speech
CNN,NN-HMMhybridrecognition;speech
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2Leveraging valence and activation information via multi-task learning for categorical emotion recognition
R. Xia, and Y. Liu. 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), page 5301--5305. IEEE, (2015)
8 years ago by @michaelneumann
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IEMOCAP,
belief
classification,
deep
emotion
multi-task,
network,
recognition,
regression
speech
IEMOCAP,beliefclassification,deepemotionmulti-task,network,recognition,regressionspeech
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2Learning salient features for speech emotion recognition using convolutional neural networks
Q. Mao, M. Dong, Z. Huang, and Y. Zhan. IEEE Transactions on Multimedia, 16 (8): 2203--2213 (2014)
8 years ago by @michaelneumann
show all tags
CNN,
DES,
Emo-DB,
MES,
SAVEE,
analysis,
classification
discriminative
emotion
feature
learning,
recognition,
salient
speech
CNN,DES,Emo-DB,MES,SAVEE,analysis,classificationdiscriminativeemotionfeaturelearning,recognition,salientspeech
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1Improving automatic emotion recognition from speech via gender differentiation
T. Vogt, and E. André. Proc. Language Resources and Evaluation Conference (LREC 2006), Genoa, (2006)
8 years ago by @michaelneumann
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Berlin
Emotion
SmartKom,
classification
database
differentiation,
emotion
emotional
gender
of
recognition,
speech
speech,
BerlinEmotionSmartKom,classificationdatabasedifferentiation,emotionemotionalgenderofrecognition,speechspeech,
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Publikationen (verstecken)36
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1Demonstration of a Serious Game for Spoken Language Experiments - GDX

2Prosodic and segmental convergence in spontaneous German conversations

1Perception‐production loop in native–non‐native dialogs: Phonetic convergence

1A 3D computer game for testing perception of acoustic detail in speech

2Individual Differences in Implicit Attention to Phonetic Detail in Speech Perception

2CoLoSS: Cognitive load corpus with speech and performance data from a symbol-digit dual-task

1Cognitive load influences performance, speech and physiological parameters in a multimodal dual-task setting

1Influences of cognitive load on learning performance, speech and physiological parameters in a dual-task setting

3Convergence of articulation rate in spontaneous speech.

2IEMOCAP: Interactive emotional dyadic motion capture database

2Speech emotion recognition using deep neural network and extreme learning machine.

2Survey on speech emotion recognition: Features, classification schemes, and databases

2Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge

1Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups

2Towards End-To-End Speech Recognition with Recurrent Neural Networks.

1Analysis of cnn-based speech recognition system using raw speech as input

2Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition

2Leveraging valence and activation information via multi-task learning for categorical emotion recognition

2Learning salient features for speech emotion recognition using convolutional neural networks

1Improving automatic emotion recognition from speech via gender differentiation

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