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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 Hits 1 – 20 of 81 1 MAGIC DUST FOR CROSS-LINGUAL ADAPTATION OF MONOLINGUAL WAV2VEC-2.0 Khurana, Sameer; Laurent, Antoine; Glass, James In: ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03544515 ; ICASSP 2022, May 2022, Singapour, Singapore (2022) BASE Show details 2 Simple and Effective Unsupervised Speech Synthesis ... Liu, Alexander H.; Lai, Cheng-I Jeff; Hsu, Wei-Ning. - : arXiv, 2022 BASE Show details 3 Learning Audio-Video Language Representations Rouditchenko, Andrew. - : Massachusetts Institute of Technology, 2021 BASE Show details 4 Cascaded Multilingual Audio-Visual Learning from Videos ... Rouditchenko, Andrew; Boggust, Angie; Harwath, David. - : arXiv, 2021 BASE Show details 5 Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0 ... Khurana, Sameer; Laurent, Antoine; Glass, James. - : arXiv, 2021 BASE Show details 6 Text-Free Image-to-Speech Synthesis Using Learned Segmental Units ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Glass, James; Harwath, David. - : Underline Science Inc., 2021 BASE Show details 7 Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Glass, James; He, Tianxing. - : Underline Science Inc., 2021 BASE Show details 8 Mitigating Biases in Toxic Language Detection through Invariant Rationalization ... Chuang, Yung-Sung; Gao, Mingye; Luo, Hongyin. - : arXiv, 2021 BASE Show details 9 Mitigating Biases in Toxic Language Detection through Invariant Rationalization ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Chen, Yun-Nung; Chuang, Yung-Sung. - : Underline Science Inc., 2021 BASE Show details 10 A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning Khurana, Sameer; Laurent, Antoine; Hsu, Wei-Ning... In: Interspeech 2020 ; https://hal.archives-ouvertes.fr/hal-02912029 ; Interspeech 2020, Oct 2020, Shanghai, China (2020) BASE Show details 11 Similarity Analysis of Contextual Word Representation Models ... Wu, John M.; Belinkov, Yonatan; Sajjad, Hassan. - : arXiv, 2020 BASE Show details 12 CSTNet: Contrastive Speech Translation Network for Self-Supervised Speech Representation Learning ... Khurana, Sameer; Laurent, Antoine; Glass, James. - : arXiv, 2020 BASE Show details 13 A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning ... Khurana, Sameer; Laurent, Antoine; Hsu, Wei-Ning. - : arXiv, 2020 BASE Show details 14 What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context ... Baly, Ramy; Karadzhov, Georgi; An, Jisun. - : arXiv, 2020 BASE Show details 15 Vector-Quantized Autoregressive Predictive Coding ... Chung, Yu-An; Tang, Hao; Glass, James. - : arXiv, 2020 BASE Show details 16 Non-Autoregressive Predictive Coding for Learning Speech Representations from Local Dependencies ... Liu, Alexander H.; Chung, Yu-An; Glass, James. - : arXiv, 2020 BASE Show details 17 Improved Speech Representations with Multi-Target Autoregressive Predictive Coding ... Chung, Yu-An; Glass, James. - : arXiv, 2020 BASE Show details 18 Classifying Alzheimer's Disease Using Audio and Text-Based Representations of Speech Haulcy, R'mani(R'mani Symon); Glass, James R In: Frontiers (2020) Abstract: Alzheimer's Disease (AD) is a form of dementia that affects the memory, cognition, and motor skills of patients. Extensive research has been done to develop accessible, cost-effective, and non-invasive techniques for the automatic detection of AD. Previous research has shown that speech can be used to distinguish between healthy patients and afflicted patients. In this paper, the ADReSS dataset, a dataset balanced by gender and age, was used to automatically classify AD from spontaneous speech. The performance of five classifiers, as well as a convolutional neural network and long short-term memory network, was compared when trained on audio features (i-vectors and x-vectors) and text features (word vectors, BERT embeddings, LIWC features, and CLAN features). The same audio and text features were used to train five regression models to predict the Mini-Mental State Examination score for each patient, a score that has a maximum value of 30. The top-performing classification models were the support vector machine and random forest classifiers trained on BERT embeddings, which both achieved an accuracy of 85.4% on the test set. The best-performing regression model was the gradient boosting regression model trained on BERT embeddings and CLAN features, which had a root mean squared error of 4.56 on the test set. The performance on both tasks illustrates the feasibility of using speech to classify AD and predict neuropsychological scores. URL: https://hdl.handle.net/1721.1/132627 BASE Hide details 19 Identification of digital voice biomarkers for cognitive health Lin, Honghuang; Karjadi, Cody; Ang, Ting F. A.... In: Explor Med (2020) BASE Show details 20 On the Linguistic Representational Power of Neural Machine Translation Models Belinkov, Yonatan; Durrani, Nadir; Dalvi, Fahim... In: Computational Linguistics, Vol 46, Iss 1, Pp 1-52 (2020) (2020) BASE Show details Page: 1 2 3 4 5

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