Papers
Learning Temporal Clusters Using Capsule Routing for Speech Emotion Recognition
Md. Asif Jalal, Erfan Loweimi, Roger K. Moore et al.
Towards Discriminative Representations and Unbiased Predictions: Class-Specific Angular Softmax for Speech Emotion Recognition
Zhixuan Li, Liang He, Jingyang Li et al.
Towards Robust Speech Emotion Recognition Using Deep Residual Networks for Speech Enhancement
Andreas Triantafyllopoulos, Gil Keren, Johannes Wagner et al.
Deep Learning of Segment-Level Feature Representation with Multiple Instance Learning for Utterance-Level Speech Emotion Recognition
Shuiyang Mao, P.C. Ching, Tan Lee
Enforcing Semantic Consistency for Cross Corpus Valence Regression from Speech Using Adversarial Discrepancy Learning
Gao-Yi Chao, Yun-Shao Lin, Chun-Min Chang et al.
Predicting Group Performances Using a Personality Composite-Network Architecture During Collaborative Task
Shun-Chang Zhong, Yun-Shao Lin, Chun-Min Chang et al.
Speech Emotion Recognition in Dyadic Dialogues with Attentive Interaction Modeling
Jinming Zhao, Shizhe Chen, Jingjun Liang et al.
Employing Bottleneck and Convolutional Features for Speech-Based Physical Load Detection on Limited Data Amounts
Olga Egorow, Tarik Mrech, Norman Weißkirchen et al.
A Path Signature Approach for Speech Emotion Recognition
Bo Wang, Maria Liakata, Hao Ni et al.
Analysis of Deep Learning Architectures for Cross-Corpus Speech Emotion Recognition
Jack Parry, Dimitri Palaz, Georgia Clarke et al.
Leveraging Acoustic Cues and Paralinguistic Embeddings to Detect Expression from Voice
Vikramjit Mitra, Sue Booker, Erik Marchi et al.
Deep Hierarchical Fusion with Application in Sentiment Analysis
Efthymios Georgiou, Charilaos Papaioannou, Alexandros Potamianos
Framewise Supervised Training Towards End-to-End Speech Recognition Models: First Results
Mohan Li, Yuanjiang Cao, Weicong Zhou et al.
Multi-Task CTC Training with Auxiliary Feature Reconstruction for End-to-End Speech Recognition
Gakuto Kurata, Kartik Audhkhasi
Exploring the Encoder Layers of Discriminative Autoencoders for LVCSR
Pin-Tuan Huang, Hung-Shin Lee, Syu-Siang Wang et al.
Two Tiered Distributed Training Algorithm for Acoustic Modeling
Pranav Ladkat, Oleg Rybakov, Radhika Arava et al.
Direct Neuron-Wise Fusion of Cognate Neural Networks
Takashi Fukuda, Masayuki Suzuki, Gakuto Kurata
Guiding CTC Posterior Spike Timings for Improved Posterior Fusion and Knowledge Distillation
Gakuto Kurata, Kartik Audhkhasi
Char+CV-CTC: Combining Graphemes and Consonant/Vowel Units for CTC-Based ASR Using Multitask Learning
Abdelwahab Heba, Thomas Pellegrini, Jean-Pierre Lorré et al.
End-to-End Automatic Speech Recognition with a Reconstruction Criterion Using Speech-to-Text and Text-to-Speech Encoder-Decoders
Ryo Masumura, Hiroshi Sato, Tomohiro Tanaka et al.
Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR
Wilfried Michel, Ralf Schlüter, Hermann Ney
Lattice-Based Lightly-Supervised Acoustic Model Training
Joachim Fainberg, Ondřej Klejch, Steve Renals et al.
Detection of Glottal Closure Instants from Raw Speech Using Convolutional Neural Networks
Mohit Goyal, Varun Srivastava, Prathosh A.P.
Whether to Pretrain DNN or not?: An Empirical Analysis for Voice Conversion
Nirmesh J. Shah, Hardik B. Sailor, Hemant A. Patil