Papers
Ideal Ratio Mask Estimation Using Deep Neural Networks for Monaural Speech Segregation in Noisy Reverberant Conditions
Xu Li, Junfeng Li, Yonghong Yan
Detecting Overlapped Speech on Short Timeframes Using Deep Learning
Valentin Andrei, Horia Cucu, Corneliu Burileanu
Variational Recurrent Neural Networks for Speech Separation
Jen-Tzung Chien, Kuan-Ting Kuo
Time-Frequency Masking for Blind Source Separation with Preserved Spatial Cues
Shadi Pirhosseinloo, Kostas Kokkinakis
Deep Clustering-Based Beamforming for Separation with Unknown Number of Sources
Takuya Higuchi, Keisuke Kinoshita, Marc Delcroix et al.
A Maximum Likelihood Approach to Deep Neural Network Based Nonlinear Spectral Mapping for Single-Channel Speech Separation
Yannan Wang, Jun Du, Li-Rong Dai et al.
Single-Ended Prediction of Listening Effort Based on Automatic Speech Recognition
Rainer Huber, Constantin Spille, Bernd T. Meyer
Humans do not Maximize the Probability of Correct Decision When Recognizing DANTALE Words in Noise
Mohsen Zareian Jahromi, Jan Østergaard, Jesper Jensen
The Recognition of Compounds: A Computational Account
L. ten Bosch, L. Boves, M. Ernestus
An Auditory Model of Speaker Size Perception for Voiced Speech Sounds
Toshio Irino, Eri Takimoto, Toshie Matsui et al.
A Comparison of Sentence-Level Speech Intelligibility Metrics
Alexander Kain, Max Del Giudice, Kris Tjaden
Google’s Next-Generation Real-Time Unit-Selection Synthesizer Using Sequence-to-Sequence LSTM-Based Autoencoders
Vincent Wan, Yannis Agiomyrgiannakis, Hanna Silen et al.
Statistical Voice Conversion with WaveNet-Based Waveform Generation
Kazuhiro Kobayashi, Tomoki Hayashi, Akira Tamamori et al.
A Hierarchical Encoder-Decoder Model for Statistical Parametric Speech Synthesis
Srikanth Ronanki, Oliver Watts, Simon King
Direct Modeling of Frequency Spectra and Waveform Generation Based on Phase Recovery for DNN-Based Speech Synthesis
Shinji Takaki, Hirokazu Kameoka, Junichi Yamagishi
Speaker-Dependent WaveNet Vocoder
Akira Tamamori, Tomoki Hayashi, Kazuhiro Kobayashi et al.
Towards Speech Emotion Recognition “in the Wild” Using Aggregated Corpora and Deep Multi-Task Learning
Jaebok Kim, Gwenn Englebienne, Khiet P. Truong et al.
Discretized Continuous Speech Emotion Recognition with Multi-Task Deep Recurrent Neural Network
Duc Le, Zakaria Aldeneh, Emily Mower Provost
Jointly Predicting Arousal, Valence and Dominance with Multi-Task Learning
Srinivas Parthasarathy, Carlos Busso
Progressive Neural Networks for Transfer Learning in Emotion Recognition
John Gideon, Soheil Khorram, Zakaria Aldeneh et al.
Interaction and Transition Model for Speech Emotion Recognition in Dialogue
Ruo Zhang, Ando Atsushi, Satoshi Kobashikawa et al.
Efficient Emotion Recognition from Speech Using Deep Learning on Spectrograms
Aharon Satt, Shai Rozenberg, Ron Hoory
Increasing Recall of Lengthening Detection via Semi-Automatic Classification
Simon Betz, Jana Voße, Sina Zarrieß et al.