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Found 22 papers, 2 papers with code
The JHU/KyotoU Speech Translation System for IWSLT 2018
This paper describes the Johns Hopkins University (JHU) and Kyoto University submissions to the Speech Translation evaluation campaign at IWSLT2018.
Empowering Federated Learning for Massive Models with NVIDIA FLARE
In the ever-evolving landscape of artificial intelligence (AI) and large language models (LLMs), handling and leveraging data effectively has become a critical challenge.
Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying
We introduce Tied-LoRA, a novel paradigm leveraging weight tying and selective training to enhance the parameter efficiency of Low-rank Adaptation (LoRA).
Multilingual Neural Machine Translation with Deep Encoder and Multiple Shallow Decoders
Recent work in multilingual translation advances translation quality surpassing bilingual baselines using deep transformer models with increased capacity.
Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation
Is bias amplified when neural machine translation (NMT) models are optimized for speed and evaluated on generic test sets using BLEU?
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data
The scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages.
XLEnt: Mining a Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment
Cross-lingual named-entity lexica are an important resource to multilingual NLP tasks such as machine translation and cross-lingual wikification.
Investigating Failures of Automatic Translation in the Case of Unambiguous Gender
Transformer based models are the modern work horses for neural machine translation (NMT), reaching state of the art across several benchmarks.
Quality Estimation without Human-labeled Data
Quality estimation aims to measure the quality of translated content without access to a reference translation.
Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms
Active learning (AL) algorithms may achieve better performance with fewer data because the model guides the data selection process.
An Exploratory Study on Multilingual Quality Estimation
Predicting the quality of machine translation has traditionally been addressed with language-specific models, under the assumption that the quality label distribution or linguistic features exhibit traits that are not shared across languages.
Spelling-Aware Construction of Macaronic Texts for Teaching Foreign-Language Vocabulary
We present a machine foreign-language teacher that modifies text in a student{'}s native language (L1) by replacing some word tokens with glosses in a foreign language (L2), in such a way that the student can acquire L2 vocabulary simply by reading the resulting macaronic text.
Simple Construction of Mixed-Language Texts for Vocabulary Learning
We accomplish this by modifying a cloze language model to incrementally learn new vocabulary items, and use this language model as a proxy for the word guessing and learning ability of real students.
A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation
Most neural machine translation systems are built upon subword units extracted by methods such as Byte-Pair Encoding (BPE) or wordpiece.
Pretraining by Backtranslation for End-to-end ASR in Low-Resource Settings
Using transcribed speech from nearby languages gives a further 20-30% relative reduction in character error rate.
Character-Aware Decoder for Translation into Morphologically Rich Languages
Neural machine translation (NMT) systems operate primarily on words (or sub-words), ignoring lower-level patterns of morphology.
ESPnet: End-to-End Speech Processing Toolkit
This paper introduces a new open source platform for end-to-end speech processing named ESPnet.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Multi-Modal Data Augmentation for End-to-End ASR
We present a new end-to-end architecture for automatic speech recognition (ASR) that can be trained using \emph{symbolic} input in addition to the traditional acoustic input.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Knowledge Tracing in Sequential Learning of Inflected Vocabulary
We present a feature-rich knowledge tracing method that captures a student{'}s acquisition and retention of knowledge during a foreign language phrase learning task.
