conftrace_

Machine Learning

121,146 papers (10 classified directly here)

Subtopics

Learning Types (52,936) Core Methods (48,729) Optimization & Theory (36,874) Application Areas (31,658) Bayesian & Probabilistic (3,963) Learning Paradigms (2,054)

Papers per year

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Papers (including subtopics)

Robust Multichannel Gender Classification from Speech in Movie Audio INTERSPEECH 2016
Fast, Compact, and High Quality LSTM-RNN Based Statistical Parametric Speech Synthesizers for Mobile Devices INTERSPEECH 2016
Model Integration for HMM- and DNN-Based Speech Synthesis Using Product-of-Experts Framework INTERSPEECH 2016
Probabilistic Amplitude Demodulation Features in Speech Synthesis for Improving Prosody INTERSPEECH 2016
On Smoothing and Enhancing Dynamics of Pitch Contours Represented by Discrete Orthogonal Polynomials for Prosody Generation INTERSPEECH 2016
An Investigation of Recurrent Neural Network Architectures Using Word Embeddings for Phrase Break Prediction INTERSPEECH 2016
Model-Based Parametric Prosody Synthesis with Deep Neural Network INTERSPEECH 2016
Active and Semi-Supervised Learning in ASR: Benefits on the Acoustic and Language Models INTERSPEECH 2016
Learning N-Gram Language Models from Uncertain Data INTERSPEECH 2016
Entropy Based Pruning for Non-Negative Matrix Based Language Models with Contextual Features INTERSPEECH 2016
Unsupervised Adaptation of Recurrent Neural Network Language Models INTERSPEECH 2016
Contextual Prediction Models for Speech Recognition INTERSPEECH 2016
Silent-Speech Command Word Recognition Using Electro-Optical Stomatography INTERSPEECH 2016
An Engine for Online Video Search in Large Archives of the Holocaust Testimonies INTERSPEECH 2016
Data Selection by Sequence Summarizing Neural Network in Mismatch Condition Training INTERSPEECH 2016
Robust Speech Recognition Using Generalized Distillation Framework INTERSPEECH 2016
Adversarial Multi-Task Learning of Deep Neural Networks for Robust Speech Recognition INTERSPEECH 2016
Two-Stage Data Augmentation for Low-Resourced Speech Recognition INTERSPEECH 2016
The Native Language Sub-Challenge: The Data INTERSPEECH 2016
Native Language Identification Using Spectral and Source-Based Features INTERSPEECH 2016
Convolutional Neural Networks with Data Augmentation for Classifying Speakers’ Native Language INTERSPEECH 2016
Multimodal Fusion of Multirate Acoustic, Prosodic, and Lexical Speaker Characteristics for Native Language Identification INTERSPEECH 2016
Exploiting Phone Log-Likelihood Ratio Features for the Detection of the Native Language of Non-Native English Speakers INTERSPEECH 2016
Determining Native Language and Deception Using Phonetic Features and Classifier Combination INTERSPEECH 2016
The INTERSPEECH 2016 Computational Paralinguistics Challenge: A Summary of Results INTERSPEECH 2016