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MAGIC DUST FOR CROSS-LINGUAL ADAPTATION OF MONOLINGUAL WAV2VEC-2.0
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In: ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03544515 ; ICASSP 2022, May 2022, Singapour, Singapore (2022)
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Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0 ...
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Text-Free Image-to-Speech Synthesis Using Learned Segmental Units ...
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Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? ...
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Mitigating Biases in Toxic Language Detection through Invariant Rationalization ...
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Mitigating Biases in Toxic Language Detection through Invariant Rationalization ...
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A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning
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In: Interspeech 2020 ; https://hal.archives-ouvertes.fr/hal-02912029 ; Interspeech 2020, Oct 2020, Shanghai, China (2020)
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Similarity Analysis of Contextual Word Representation Models ...
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Abstract:
This paper investigates contextual word representation models from the lens of similarity analysis. Given a collection of trained models, we measure the similarity of their internal representations and attention. Critically, these models come from vastly different architectures. We use existing and novel similarity measures that aim to gauge the level of localization of information in the deep models, and facilitate the investigation of which design factors affect model similarity, without requiring any external linguistic annotation. The analysis reveals that models within the same family are more similar to one another, as may be expected. Surprisingly, different architectures have rather similar representations, but different individual neurons. We also observed differences in information localization in lower and higher layers and found that higher layers are more affected by fine-tuning on downstream tasks. ... : Accepted to ACL 2020 ...
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Keyword:
68T50; Computation and Language cs.CL; FOS Computer and information sciences; I.2.7
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URL: https://arxiv.org/abs/2005.01172 https://dx.doi.org/10.48550/arxiv.2005.01172
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CSTNet: Contrastive Speech Translation Network for Self-Supervised Speech Representation Learning ...
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A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning ...
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What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context ...
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Non-Autoregressive Predictive Coding for Learning Speech Representations from Local Dependencies ...
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Improved Speech Representations with Multi-Target Autoregressive Predictive Coding ...
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Classifying Alzheimer's Disease Using Audio and Text-Based Representations of Speech
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In: Frontiers (2020)
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Identification of digital voice biomarkers for cognitive health
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In: Explor Med (2020)
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On the Linguistic Representational Power of Neural Machine Translation Models
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In: Computational Linguistics, Vol 46, Iss 1, Pp 1-52 (2020) (2020)
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