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Neural Networks

11300 directly classified papers

Papers per year

Papers

CTC in the Context of Generalized Full-Sum HMM Training INTERSPEECH 2017
Reducing the Computational Complexity of Two-Dimensional LSTMs INTERSPEECH 2017
Deep Neural Network Embeddings for Text-Independent Speaker Verification INTERSPEECH 2017
A Hierarchical Encoder-Decoder Model for Statistical Parametric Speech Synthesis INTERSPEECH 2017
Deep Clustering-Based Beamforming for Separation with Unknown Number of Sources INTERSPEECH 2017
Variational Recurrent Neural Networks for Speech Separation INTERSPEECH 2017
Ideal Ratio Mask Estimation Using Deep Neural Networks for Monaural Speech Segregation in Noisy Reverberant Conditions INTERSPEECH 2017
Parallel-Data-Free Many-to-Many Voice Conversion Based on DNN Integrated with Eigenspace Using a Non-Parallel Speech Corpus INTERSPEECH 2017
Stochastic Recurrent Neural Network for Speech Recognition INTERSPEECH 2017
Frame and Segment Level Recurrent Neural Networks for Phone Classification INTERSPEECH 2017
Deep Speaker Feature Learning for Text-Independent Speaker Verification INTERSPEECH 2017
Duration Mismatch Compensation Using Four-Covariance Model and Deep Neural Network for Speaker Verification INTERSPEECH 2017
i-Vector DNN Scoring and Calibration for Noise Robust Speaker Verification INTERSPEECH 2017
A Comparative Evaluation of GMM-Free State Tying Methods for ASR INTERSPEECH 2017
Sequence to Sequence Modeling for User Simulation in Dialog Systems INTERSPEECH 2017
A Fast and Lightweight System for Multilingual Dependency Parsing CONLL 2017
CLCL (Geneva) DINN Parser: a Neural Network Dependency Parser Ten Years Later CONLL 2017
Initial Explorations of CCG Supertagging for Universal Dependency Parsing CONLL 2017
A non-projective greedy dependency parser with bidirectional LSTMs CONLL 2017
A Novel Neural Network Model for Joint POS Tagging and Graph-based Dependency Parsing CONLL 2017
Parsing with Context Embeddings CONLL 2017
A System for Multilingual Dependency Parsing based on Bidirectional LSTM Feature Representations CONLL 2017
The HIT-SCIR System for End-to-End Parsing of Universal Dependencies CONLL 2017
Stanford’s Graph-based Neural Dependency Parser at the CoNLL 2017 Shared Task CONLL 2017
A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling CONLL 2017