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Negative language transfer in learner English: A new dataset ...
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Parallel sentences mining with transfer learning in an unsupervised setting ...
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Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation ...
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Abstract:
Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.150/ Abstract: A conventional approach to improving the performance of end-to-end speech translation (E2E-ST) models is to leverage the source transcription via pre-training and joint training with automatic speech recognition (ASR) and neural machine translation (NMT) tasks. However, since the input modalities are different, it is difficult to leverage source language text successfully. In this work, we focus on sequence-level knowledge distillation (SeqKD) from external text-based NMT models. To leverage the full potential of the source language information, we propose backward SeqKD, SeqKD from a target-to-source backward NMT model. To this end, we train a bilingual E2E-ST model to predict paraphrased transcriptions as an auxiliary task with a single decoder. The paraphrases are generated from the translations in bitext via back-translation. We further propose bidirectional SeqKD in which SeqKD from both forward and ...
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Keyword:
Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing
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URL: https://underline.io/lecture/19964-source-and-target-bidirectional-knowledge-distillation-for-end-to-end-speech-translation https://dx.doi.org/10.48448/ns3s-q953
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Detoxifying Language Models Risks Marginalizing Minority Voices ...
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Domain Adaptation for Arabic Cross-Domain and Cross-Dialect Sentiment Analysis from Contextualized Word Embedding ...
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Knowledge Enhanced Masked Language Model for Stance Detection ...
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LIVE SESSION: 15D-Oral: Phonology, Morphology and Word Segmentation ...
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How low is too low? A monolingual take on lemmatisation in Indian languages ...
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Frustratingly Easy Edit-based Linguistic Steganography with a Masked Language Model ...
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MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories ...
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A Global Past-Future Early Exit Method for Accelerating Inference of Pre-trained Language Models ...
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DirectProbe: Studying Representations without Classifiers ...
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Challenging distributional models with a conceptual network of philosophical terms ...
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ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding ...
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Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems ...
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CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems ...
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multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning ...
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