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Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
We propose Deep Autoencoding Predictive Components (DAPC) – a self-super...
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A Comparison of Pooling Methods on LSTM Models for Rare Acoustic Event Classification
Acoustic event classification (AEC) and acoustic event detection (AED) r...
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Unsupervised Pre-training of Bidirectional Speech Encoders via Masked Reconstruction
We propose an approach for pre-training speech representations via a mas...
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Data Techniques For Online End-to-end Speech Recognition
Practitioners often need to build ASR systems for new use cases in a sho...
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Semi-supervised ASR by End-to-end Self-training
While deep learning based end-to-end automatic speech recognition (ASR) ...
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Acoustic scene analysis with multi-head attention networks
Acoustic Scene Classification (ASC) is a challenging task, as a single s...
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Multimodal and Multi-view Models for Emotion Recognition
Studies on emotion recognition (ER) show that combining lexical and acou...
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Everything old is new again: A multi-view learning approach to learning using privileged information and distillation
We adopt a multi-view approach for analyzing two knowledge transfer sett...
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A simple model for detection of rare sound events
We propose a simple recurrent model for detecting rare sound events, whe...
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R-CRNN: Region-based Convolutional Recurrent Neural Network for Audio Event Detection
This paper proposes a Region-based Convolutional Recurrent Neural Networ...
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Acoustic feature learning using cross-domain articulatory measurements
Previous work has shown that it is possible to improve speech recognitio...
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Acoustic feature learning cross-domain articulatory measurements
Previous work has shown that it is possible to improve speech recognitio...
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Distributed Stochastic Multi-Task Learning with Graph Regularization
We propose methods for distributed graph-based multi-task learning that ...
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Acoustic Feature Learning via Deep Variational Canonical Correlation Analysis
We study the problem of acoustic feature learning in the setting where w...
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Efficient coordinate-wise leading eigenvector computation
We develop and analyze efficient "coordinate-wise" methods for finding t...
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Stochastic Canonical Correlation Analysis
We tightly analyze the sample complexity of CCA, provide a learning algo...
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Multi-view Recurrent Neural Acoustic Word Embeddings
Recent work has begun exploring neural acoustic word embeddings---fixed-...
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End-to-End Training Approaches for Discriminative Segmental Models
Recent work on discriminative segmental models has shown that they can a...
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Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation
We study the problem of recognizing video sequences of fingerspelled let...
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Efficient Segmental Cascades for Speech Recognition
Discriminative segmental models offer a way to incorporate flexible feat...
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Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation
We study the problem of recognition of fingerspelled letter sequences in...
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Network Inference by Learned Node-Specific Degree Prior
We propose a novel method for network inference from partially observed ...
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On Column Selection in Approximate Kernel Canonical Correlation Analysis
We study the problem of column selection in large-scale kernel canonical...
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Nonparametric Canonical Correlation Analysis
Canonical correlation analysis (CCA) is a classical representation learn...
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Deep convolutional acoustic word embeddings using word-pair side information
Recent studies have been revisiting whole words as the basic modelling u...
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Discriminative Segmental Cascades for Feature-Rich Phone Recognition
Discriminative segmental models, such as segmental conditional random fi...
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The role of dimensionality reduction in linear classification
Dimensionality reduction (DR) is often used as a preprocessing step in c...
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LASS: a simple assignment model with Laplacian smoothing
We consider the problem of learning soft assignments of N items to K cat...
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Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application
We provide an elementary proof of a simple, efficient algorithm for comp...
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The K-modes algorithm for clustering
Many clustering algorithms exist that estimate a cluster centroid, such ...
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Distributed optimization of deeply nested systems
In science and engineering, intelligent processing of complex signals su...
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