Introduction of the Asian Language Treebank

By Hammam Riza, Michael Purwoadi, Gunarso, Teduh Uliniansyah, Aw Ai Ti, Sharifah Mahani Aljunied, Luong Chi Mai, Vu Tat Thang, Nguyen Phuong Thai, Vichet Chea and 7 more. 2016

90 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Natural Language Processing, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Natural Language Processing

In Evaluation & Benchmarks

Citations in the corpus

Beyond English-Centric Multilingual Machine Translation (2020, methodology): “Other lines of work present resources for low-resource Asian languages, such as the ALT project (Riza et al., 2016; Ding et al., 2016), Mongolian, Uyghur, and Tibetian (Anonymous, 2020), or strategies for improvement on specific directions (Chen et al., 2019).”
The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English (2019, background): “More recently, the Asian Language Treebank project (Riza et al., 2016) has introduced parallel datasets for several low-resource language pairs, but these are sampled from text originating in English and thus may not generalize to text sampled from low-resource languages.”
Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English (2019, background): “More recently, the Asian Language Treebank project (Riza et al., 2016) has introduced parallel data-sets for several low-resource language pairs, but these are sampled from text originating in English and thus may not generalize to text sampled from low-resource languages.”
Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation (2019, background): “While NMT is known to perform well for resource-rich language pairs, such as French– English and German–English (Bojar et al., 2018), it performs poorly for resource-poor pairs (Zoph et al., 2016; Riza et al., 2016).”
Towards Burmese (Myanmar) Morphological Analysis (2019, result): “An overview of the ALT project and international collaboration can be found in the report by Riza et al. [36].”
Similar Southeast Asian Languages: Corpus-Based Case Study on Thai-Laotian and Malay-Indonesian (2016, background): “The Asian Language Treebank (ALT) 1 (Utiyama and Sumita, 2015; Riza et al., 2016), containing approximately 20 , 000 parallel sentence pairs on several Asian languages, facilitates statistical approaches.”
Softmax Tempering for Training Neural Machine Translation Models (2020, background): “Figure 4 shows the BLEU scores for all the 22 translation directions in the ALT translation tasks.”