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Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech
Research article (2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), 2015) · cited 88× · AI/ML
Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech
Summary
Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech is a scholarly article[1].
Key Facts
Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech. Retrieved May 24, 2026, from https://4ort.xyz/entity/using-bidirectional-lstm-recurrent-neural-networks-to-learn-high-level-abstractions-of-sequential-features-for-automated
MLA“Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/using-bidirectional-lstm-recurrent-neural-networks-to-learn-high-level-abstractions-of-sequential-features-for-automated.
BibTeX@misc{4ortxyz_using-bidirectional-lstm-recurrent-neural-networks-to-learn-high-level-abstractions-of-sequential-features-for-automated_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech}}, year = {2026}, url = {https://4ort.xyz/entity/using-bidirectional-lstm-recurrent-neural-networks-to-learn-high-level-abstractions-of-sequential-features-for-automated}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech — https://4ort.xyz/entity/using-bidirectional-lstm-recurrent-neural-networks-to-learn-high-level-abstractions-of-sequential-features-for-automated (retrieved 2026-05-24)
