1 |
The effect of domain and diacritics in Yorùbá-English neural machine translation
|
|
|
|
In: 18th Biennial Machine Translation Summit ; https://hal.inria.fr/hal-03350967 ; 18th Biennial Machine Translation Summit, Aug 2021, Orlando, United States (2021)
|
|
BASE
|
|
Show details
|
|
5 |
A Data Augmentation Approach for Sign-Language-To-Text Translation In-The-Wild ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages ...
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Automatic classification of human translation and machine translation : a study from the perspective of lexical diversity
|
|
|
|
BASE
|
|
Show details
|
|
11 |
Tailoring and Evaluating the Wikipedia for in-Domain Comparable Corpora Extraction ...
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Multilingual and Interlingual Semantic Representations for Natural Language Processing: A Brief Introduction
|
|
|
|
In: Computational Linguistics, Vol 46, Iss 2, Pp 249-255 (2020) (2020)
|
|
BASE
|
|
Show details
|
|
18 |
GeBioToolkit: Automatic Extraction of Gender-Balanced Multilingual Corpus of Wikipedia Biographies ...
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi ...
|
|
|
|
BASE
|
|
Show details
|
|
20 |
Query Translation for Cross-lingual Search in the Academic Search Engine PubPsych ...
|
|
|
|
Abstract:
We describe a lexical resource-based process for query translation of a domain-specific and multilingual academic search engine in psychology, PubPsych. PubPsych queries are diverse in language with a high amount of informational queries and technical terminology. We present an approach for translating queries into English, German, French, and Spanish. We build a quadrilingual lexicon with aligned terms in the four languages using MeSH, Wikipedia and Apertium as our main resources. Our results show that using the quadlexicon together with some simple translation rules, we can automatically translate 85% of translatable tokens in PubPsych queries with mean adequacy over all the translatable text of 1.4 when measured on a 3-point scale [0,1,2]. ...
|
|
Keyword:
150; information retrieval; machine translation
|
|
URL: https://dx.doi.org/10.23668/psycharchives.928 https://www.psycharchives.org/handle/20.500.12034/735
|
|
BASE
|
|
Hide details
|
|
|
|