SLUE: New Benchmark Tasks For Spoken Language Understanding Evaluation on Natural Speech. | 0 | 0.34 | 2022 |
Editorial Editorial of Special Issue on Self-Supervised Learning for Speech and Audio Processing | 0 | 0.34 | 2022 |
On the Use of External Data for Spoken Named Entity Recognition | 0 | 0.34 | 2022 |
Searching for fingerspelled content in American Sign Language | 0 | 0.34 | 2022 |
Self-Supervised Speech Representation Learning: A Review | 0 | 0.34 | 2022 |
Chess as a Testbed for Language Model State Tracking. | 0 | 0.34 | 2022 |
Substructure Distribution Projection for Zero-Shot Cross-Lingual Dependency Parsing | 0 | 0.34 | 2022 |
Substructure Substitution - Structured Data Augmentation for NLP. | 0 | 0.34 | 2021 |
Learning Speech Models from Multi-Modal Data. | 0 | 0.34 | 2021 |
Whole-Word Segmental Speech Recognition with Acoustic Word Embeddings | 0 | 0.34 | 2021 |
LAYER-WISE ANALYSIS OF A SELF-SUPERVISED SPEECH REPRESENTATION MODEL | 0 | 0.34 | 2021 |
Acoustic Span Embeddings For Multilingual Query-By-Example Search | 0 | 0.34 | 2021 |
Fingerspelling Detection in American Sign Language | 0 | 0.34 | 2021 |
On the Role of Supervision in Unsupervised Constituency Parsing. | 0 | 0.34 | 2020 |
Multilingual Jointly Trained Acoustic and Written Word Embeddings | 0 | 0.34 | 2020 |
PeTra: A Sparsely Supervised Memory Model for People Tracking | 0 | 0.34 | 2020 |
Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks. | 0 | 0.34 | 2020 |
Discrete Latent Variable Representations for Low-Resource Text Classification | 0 | 0.34 | 2020 |
Acoustically Grounded Word Embeddings For Improved Acoustics-To-Word Speech Recognition | 0 | 0.34 | 2019 |
On the Contributions of Visual and Textual Supervision in Low-resource Semantic Speech Retrieval. | 1 | 0.34 | 2019 |
Semantic Speech Retrieval With a Visually Grounded Model of Untranscribed Speech. | 4 | 0.40 | 2019 |
Pre-Trained Text Embeddings for Enhanced Text-to-Speech Synthesis | 0 | 0.34 | 2019 |
Pre-training on high-resource speech recognition improves low-resource speech-to-text translation. | 1 | 0.36 | 2018 |
Hierarchical Multitask Learning for CTC-based Speech Recognition. | 1 | 0.37 | 2018 |
A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech Recognition. | 4 | 0.40 | 2018 |
Variational Sequential Labelers for Semi-Supervised Learning. | 0 | 0.34 | 2018 |
American Sign Language fingerspelling recognition in the wild. | 1 | 0.41 | 2018 |
Parsing Speech: a Neural Approach to Integrating Lexical and Acoustic-Prosodic Information. | 2 | 0.37 | 2018 |
End-to-End Neural Segmental Models for Speech Recognition. | 4 | 0.46 | 2017 |
Multi-view Recurrent Neural Acoustic Word Embeddings. | 0 | 0.34 | 2017 |
Acoustic Feature Learning Via Deep Variational Canonical Correlation Analysis | 1 | 0.37 | 2017 |
Multitask training with unlabeled data for end-to-end sign language fingerspelling recognition | 1 | 0.36 | 2017 |
Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation. | 3 | 0.43 | 2017 |
Learning to Embed Words in Context for Syntactic Tasks. | 3 | 0.65 | 2017 |
Semantic keyword spotting by learning from images and speech. | 0 | 0.34 | 2017 |
Multitask Learning With Low-Level Auxiliary Tasks For Encoder-Decoder Based Speech Recognition | 10 | 0.54 | 2017 |
An Embedded Segmental K-Means Model For Unsupervised Segmentation And Clustering Of Speech | 4 | 0.37 | 2017 |
Joint Modeling of Text and Acoustic-Prosodic Cues for Neural Parsing. | 0 | 0.34 | 2017 |
Speech Production in Speech Technologies: Introduction to the CSL Special Issue | 1 | 0.36 | 2016 |
Multi-view Recurrent Neural Acoustic Word Embeddings. | 0 | 0.34 | 2016 |
Discriminative acoustic word embeddings: Tecurrent neural network-based approaches | 0 | 0.34 | 2016 |
Discriminative Acoustic Word Embeddings: Recurrent Neural Network-Based Approaches | 0 | 0.34 | 2016 |
Jointly learning to align and convert graphemes to phonemes with neural attention models | 1 | 0.40 | 2016 |
Nonparametric Canonical Correlation Analysis. | 12 | 0.65 | 2016 |
Charagram: Embedding Words and Sentences via Character n-grams. | 39 | 1.49 | 2016 |
Deep Variational Canonical Correlation Analysis. | 13 | 0.60 | 2016 |
On Deep Multi-View Representation Learning: Objectives and Optimization. | 5 | 0.43 | 2016 |
Mapping Unseen Words to Task-Trained Embedding Spaces. | 2 | 0.39 | 2016 |
Large-Scale Approximate Kernel Canonical Correlation Analysis | 0 | 0.34 | 2016 |
End-to-end training approaches for discriminative segmental models | 3 | 0.37 | 2016 |