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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Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Intent Detection ATIS DELTA (BLSTM-CRF) Accuracy 97.40 # 10
F1 0.952 # 9
Abstractive Text Summarization CNN / Daily Mail DELTA (BLSTM) ROUGE-L 27.3 # 47
Named Entity Recognition (NER) CoNLL 2003 (English) DELTA (NER ELMO) F1 92.2 # 43
Named Entity Recognition (NER) CoNLL 2003 (English) DELTA (NER BLSTM-CRF) F1 84.6 # 71
Natural Language Inference SNLI DELTA (LSTM) % Test Accuracy 80.7 # 90
Text Classification TREC-6 DELTA (CNN) Error 7.8 # 15
Text Classification Yahoo! Answers DELTA (HAN) Accuracy 75.1 # 3


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