Papers › DELTA: A DEep learning based Language Technology plAtform
DELTA: A DEep learning based Language Technology plAtform
Kun Han, Junwen Chen, HUI ZHANG, Haiyang Xu, Yiping Peng, Yun Wang, Ning Ding, Hui Deng, Yonghu Gao, Tingwei Guo, Yi Zhang, Yahao He, Baochang Ma, Yu-Long Zhou, Kangli Zhang, Chao Liu, Ying Lyu, Chenxi Wang, Cheng Gong, Yunbo Wang, Wei Zou, Hui Song, Xiangang Li
In this paper we present DELTA, a deep learning based language technology platform. DELTA is an end-to-end platform designed to solve industry level natural language and speech processing problems. It integrates most popular neural network models for training as well as comprehensive deployment tools for production. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. We demonstrate the reliable performance with DELTA on several natural language processing and speech tasks, including text classification, named entity recognition, natural language inference, speech recognition, speaker verification, etc. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Abstractive Text Summarization | CNN / Daily Mail | DELTA (BLSTM) | ROUGE-L | 27.3 | #53 of 53 | Archive leaderboard | report |
| Intent Detection | ATIS | DELTA (BLSTM-CRF) | Accuracy | 97.40 | #12 of 16 | Archive leaderboard | report |
| Natural Language Inference | SNLI | DELTA (LSTM) | % Test Accuracy | 80.7 | #89 of 98 | Archive leaderboard | report |
| Slot Filling | ATIS | DELTA (BLSTM-CRF) | F1 | 0.952 | #12 of 14 | Archive leaderboard | report |
| Text Classification | TREC-6 | DELTA (CNN) | Error | 7.8 | #17 of 19 | Archive leaderboard | report |
| Text Classification | Yahoo! Answers | DELTA (HAN) | Accuracy | 75.1 | #3 of 10 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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