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)

Generation and Pruning of Pronunciation Variants to Improve ASR Accuracy INTERSPEECH 2016
Optimizing Speech Recognition Evaluation Using Stratified Sampling INTERSPEECH 2016
Context Aware Mispronunciation Detection for Mandarin Pronunciation Training INTERSPEECH 2016
DNN Online with iVectors Acoustic Modeling and Doc2Vec Distributed Representations for Improving Automated Speech Scoring INTERSPEECH 2016
Detecting Mispronunciations of L2 Learners and Providing Corrective Feedback Using Knowledge-Guided and Data-Driven Decision Trees INTERSPEECH 2016
HMM-Based Non-Native Accent Assessment Using Posterior Features INTERSPEECH 2016
Automatic Assessment and Error Detection of Shadowing Speech: Case of English Spoken by Japanese Learners INTERSPEECH 2016
Multiplicity of the Acoustic Correlates of the Fortis-Lenis Contrast: Plosives in Aberystwyth English INTERSPEECH 2016
Automatic Measurement of Voice Onset Time and Prevoicing Using Recurrent Neural Networks INTERSPEECH 2016
Classification of Voice Modality Using Electroglottogram Waveforms INTERSPEECH 2016
Voice-Quality Difference Between the Vowels in Filled Pauses and Ordinary Lexical Items INTERSPEECH 2016
Generation of Emotion Control Vector Using MDS-Based Space Transformation for Expressive Speech Synthesis INTERSPEECH 2016
Direct Expressive Voice Training Based on Semantic Selection INTERSPEECH 2016
A Hybrid System for Continuous Word-Level Emphasis Modeling Based on HMM State Clustering and Adaptive Training INTERSPEECH 2016
Results of The 2015 NIST Language Recognition Evaluation INTERSPEECH 2016
The 2015 NIST Language Recognition Evaluation: The Shared View of I2R, Fantastic4 and SingaMS INTERSPEECH 2016
Pair-Wise Distance Metric Learning of Neural Network Model for Spoken Language Identification INTERSPEECH 2016
Non-Iterative Parameter Estimation for Total Variability Model Using Randomized Singular Value Decomposition INTERSPEECH 2016
A Divide-and-Conquer Approach for Language Identification Based on Recurrent Neural Networks INTERSPEECH 2016
Context-Sensitive and Role-Dependent Spoken Language Understanding Using Bidirectional and Attention LSTMs INTERSPEECH 2016
A Step Beyond Local Observations with a Dialog Aware Bidirectional GRU Network for Spoken Language Understanding INTERSPEECH 2016
Sequential Convolutional Neural Networks for Slot Filling in Spoken Language Understanding INTERSPEECH 2016
A New Pre-Training Method for Training Deep Learning Models with Application to Spoken Language Understanding INTERSPEECH 2016
Joint Syntactic and Semantic Analysis with a Multitask Deep Learning Framework for Spoken Language Understanding INTERSPEECH 2016
Exploiting Hidden-Layer Responses of Deep Neural Networks for Language Recognition INTERSPEECH 2016