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Speech emotion recognition is a challenging task, and extensive reliance has been placed on models that use audio features in building well-performing classifiers.
“Hidden markov model-based speech emotion recognition,”
Björn Schuller, Gerhard Rigoll, and Manfred Lang, · 2003
Earlier work this paper cites.
“Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine-belief network architecture,”
Björn Schuller, Gerhard Rigoll, and Manfred Lang, · 2004
Earlier work this paper cites.
“Nltk: the natural language toolkit,”
Steven Bird and Edward Loper, · 2004
Earlier work this paper cites.
“Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks,”
Alex Graves, Santiago Fernández, Faustino Gomez, and Jürgen Schmidhuber, · 2006
Earlier work this paper cites.
“Constructing the affective lexicon ontology,”
Linhong Xu, Hongfei Lin, Yu Pan, Hui Ren, and Jianmei Chen, · 2008
Earlier work this paper cites.
“Iemocap: Interactive emotional dyadic motion capture database,”
Carlos Busso, Murtaza Bulut, Chi-Chun Lee, Abe Kazemzadeh, Emily Mower, Samuel Kim, Jeannette N Chang, Sungbok Lee, and Shrikanth S Narayanan, · 2008
Earlier work this paper cites.
“Emotion recognition using a hierarchical binary decision tree approach,”
Chi-Chun Lee, Emily Mower, Carlos Busso, Sungbok Lee, and Shrikanth Narayanan, · 2011
Earlier work this paper cites.
“Imagenet classification with deep convolutional neural networks,”
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton, · 2012
Earlier work this paper cites.
“Speech emotion recognition using support vector machines,”
Thapanee Seehapoch and Sartra Wongthanavasu, · 2013
Earlier work this paper cites.
“Recent developments in opensmile, the munich open-source multimedia feature extractor,”
Florian Eyben, Felix Weninger, Florian Gross, and Björn Schuller, · 2013
Earlier work this paper cites.
“Exact solutions to the nonlinear dynamics of learning in deep linear neural networks,”
Andrew M Saxe, James L McClelland, and Surya Ganguli, · 2013
Earlier work this paper cites.
“Neural machine translation by jointly learning to align and translate,”
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio, · 2014
Earlier work this paper cites.
“Toward effective automatic recognition systems of emotion in speech,”
Carlos Busso, Murtaza Bulut, and Shrikanth Narayanan, · 2014
Cited alongside, same era.
“Speech emotion recognition using deep neural network and extreme learning machine,”
Kun Han, Dong Yu, and Ivan Tashev, · 2014
Cited alongside, same era.
“Empirical evaluation of gated recurrent neural networks on sequence modeling,”
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio, · 2014
Cited alongside, same era.
“Glove: Global vectors for word representation,”
Jeffrey Pennington, Richard Socher, and Christopher Manning, · 2014
Cited alongside, same era.
“Effective approaches to attention-based neural machine translation,”
Thang Luong, Hieu Pham, and Christopher D Manning, · 2015
Cited alongside, same era.
“Using regional saliency for speech emotion recognition,”
Zakaria Aldeneh and Emily Mower Provost, · 2017
Later among the works it cites.
“Efficient emotion recognition from speech using deep learning on spectrograms,”
Aharon Satt, Shai Rozenberg, and Ron Hoory, · 2017
Later among the works it cites.
“Towards speech emotion recognition” in the wild” using aggregated corpora and deep multi-task learning,”
Jaebok Kim, Gwenn Englebienne, Khiet P Truong, and Vanessa Evers, · 2017
Later among the works it cites.
“Progressive neural networks for transfer learning in emotion recognition,”
John Gideon, Soheil Khorram, Zakaria Aldeneh, Dimitrios Dimitriadis, and Emily Mower Provost, · 2017
Later among the works it cites.
“Salience based lexical features for emotion recognition,”
Kalani Wataraka Gamage, Vidhyasaharan Sethu, and Eliathamby Ambikairajah, · 2017
Later among the works it cites.
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Jinkyu Lee and Ivan Tashev, · 2015
Cited alongside, same era.
“Deep speech 2: End-to-end speech recognition in english and mandarin,”
Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Qiang Cheng, Guoliang Chen, et al., · 2016
Cited alongside, same era.
AUTOMATIC SPEECH RECOGNITION
Dong Yu and Li Deng, · 2016
Cited alongside, same era.
“Audio-based multimedia event detection using deep recurrent neural networks,”
Yun Wang, Leonardo Neves, and Florian Metze, · 2016
Cited alongside, same era.
“A first look into a convolutional neural network for speech emotion detection,”
Dario Bertero and Pascale Fung, · 2017
Cited alongside, same era.
“Speech emotion recognition from spectrograms with deep convolutional neural network,”
Abdul Malik Badshah, Jamil Ahmad, Nasir Rahim, and Sung Wook Baik, · 2017
Cited alongside, same era.
Seyedmahdad Mirsamadi, Emad Barsoum, and Cha Zhang, · 2017
Later among the works it cites.
“Attentive convolutional neural network based speech emotion recognition: A study on the impact of input features, signal length, and acted speech,”
Michael Neumann and Ngoc Thang Vu, · 2017
Later among the works it cites.
“Emotional chatting machine: Emotional conversation generation with internal and external memory,” 2018
Hao Zhou, Minlie Huang, Tianyang Zhang, Xiaoyan Zhu, and Bing Liu, · 2018
Closest in time.
“Automatic dialogue generation with expressed emotions,”
Chenyang Huang, Osmar Zaiane, Amine Trabelsi, and Nouha Dziri, · 2018
Closest in time.
“Cloud speech-to-text,” http://cloud.google.com/speech-to-text/, 2018
Google, · 2018
Closest in time.
“Microsoft speech api,” http://docs.microsoft.com/en-us/azure/cognitive-services/speech/home, 2018
Microsoft, · 2018
Closest in time.