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Found 7 papers, 0 papers with code
Multiple Captions Embellished Multilingual Multi-Modal Neural Machine Translation
In this work, we utilise the multiple captions from the Multi-30K dataset to increase the lexical diversity aided with the cross-lingual transfer of information among the languages in a multilingual setup.
Low Resource Multimodal Neural Machine Translation of English-Hindi in News Domain
The parallel corpus is used to train the English-Hindi Neural Machine Translation (NMT) and an English-Hindi MMT system by incorporating the image feature paired with the corresponding parallel corpus.
English to Manipuri and Mizo Post-Editing Effort and its Impact on Low Resource Machine Translation
A Computer Assisted Translation (CAT) tool is used to record the time, keystroke and other indicators to measure PE effort in terms of temporal and technical effort.
An Experiment on Speech-to-Text Translation Systems for Manipuri to English on Low Resource Setting
Based on this dataset, a benchmark evaluation is reported for the Manipuri-English Speech-to-Text translation using two approaches: 1) a pipeline model consisting of ASR (Automatic Speech Recognition) and Machine translation, and 2) an end-to-end Speech-to-Text translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
On the Transferability of Massively Multilingual Pretrained Models in the Pretext of the Indo-Aryan and Tibeto-Burman Languages
In recent times, machine translation models can learn to perform implicit bridging between language pairs never seen explicitly during training and showing that transfer learning helps for languages with constrained resources.
An Efficient Keyframes Selection Based Framework for Video Captioning
Describing a video is a challenging yet attractive task since it falls into the intersection of computer vision and natural language generation.
Ranked #1 on
Video Captioning
on Hindi MSR-VTT
WAT2019: English-Hindi Translation on Hindi Visual Genome Dataset
In this paper, we carried out an extensive comparison to evaluate the benefits of using a multimodal approach on translating text in English to a low resource language, Hindi as a part of WAT2019 shared task.
