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Spoken Language Understanding

Papers

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Showing 201–250 of 550 papers

TitleStatusHype
Distributionally Robust Finetuning BERT for Covariate Drift in Spoken Language Understanding—0
End-to-end Spoken Conversational Question Answering: Task, Dataset and Model—0
WaBERT: A Low-resource End-to-end Model for Spoken Language Understanding and Speech-to-BERT Alignment—0
Blockwise Streaming Transformer for Spoken Language Understanding and Simultaneous Speech Translation—0
GL-CLeF: A Global-Local Contrastive Learning Framework for Cross-lingual Spoken Language UnderstandingCode0
Towards End-to-End Integration of Dialog History for Improved Spoken Language Understanding—0
Building an ASR Error Robust Spoken Virtual Patient System in a Highly Class-Imbalanced Scenario Without Speech Data—0
Tokenwise Contrastive Pretraining for Finer Speech-to-BERT Alignment in End-to-End Speech-to-Intent Systems—0
A Study of Different Ways to Use The Conformer Model For Spoken Language Understanding—0
Three-Module Modeling For End-to-End Spoken Language Understanding Using Pre-trained DNN-HMM-Based Acoustic-Phonetic Model—0
Deliberation Model for On-Device Spoken Language Understanding—0
End-to-end model for named entity recognition from speech without paired training data—0
Multi-task RNN-T with Semantic Decoder for Streamable Spoken Language Understanding—0
Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis—0
Towards Reducing the Need for Speech Training Data To Build Spoken Language Understanding Systems—0
Knowledge Augmented BERT Mutual Network in Multi-turn Spoken Dialogues—0
Improving End-to-End Models for Set Prediction in Spoken Language Understanding—0
Dialog Intent Induction via Density-based Deep Clustering Ensemble—0
Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent DetectionCode0
On the Use of External Data for Spoken Named Entity RecognitionCode0
Attentive Contextual Carryover for Multi-Turn End-to-End Spoken Language Understanding—0
Training data reduction for multilingual Spoken Language Understanding systems—0
Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?—0
Lattention: Lattice-attention in ASR rescoring—0
Inducing Global and Local Knowledge Attention in Multi-turn Dialog Understanding—0
On Spoken Language Understanding Systems for Low Resourced Languages—0
A Graph-to-Sequence Model for Joint Intent Detection and Slot Filling in Task-Oriented Dialogue Systems—0
A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding—0
Feedback Attribution for Counterfactual Bandit Learning in Multi-Domain Spoken Language Understanding—0
What BERT Based Language Model Learns in Spoken Transcripts: An Empirical Study—0
FANS: Fusing ASR and NLU for on-device SLU—0
Intent Classification Using Pre-trained Language Agnostic Embeddings For Low Resource Languages—0
Speech Summarization using Restricted Self-Attention—0
Deciding Whether to Ask Clarifying Questions in Large-Scale Spoken Language Understanding—0
What BERT Based Language Models Learn in Spoken Transcripts: An Empirical Study—0
Towards Joint Intent Detection and Slot Filling via Higher-order Attention—0
Multimodal Audio-textual Architecture for Robust Spoken Language Understanding—0
A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act DetectionCode0
Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding—0
HAN: Higher-order Attention Network for Spoken Language Understanding—0
Augmenting Slot Values and Contexts for Spoken Language Understanding with Pretrained ModelsCode0
Integrating Dialog History into End-to-End Spoken Language Understanding Systems—0
An Effective Non-Autoregressive Model for Spoken Language Understanding—0
Learning a Neural Diff for Speech Models—0
面向中文口语理解的基于依赖引导的字特征槽填充模型(A Dependency-Guided Character-Based Slot Filling Model for Chinese Spoken Language Understanding)—0
Combining semantic search and twin product classification for recognition of purchasable items in voice shopping—0
A Joint and Domain-Adaptive Approach to Spoken Language Understanding—0
Learning De-identified Representations of Prosody from Raw Audio—0
Unsupervised Spoken Utterance Classification—0
Word-Free Spoken Language Understanding for Mandarin-Chinese—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Finstreder (Conformer + AMT, character-based)Accuracy (%)99.8—Unverified
2UniverSLUAccuracy (%)99.8—Unverified
3E2E SLP two-stepAccuracy (%)99.7—Unverified
4textual-kd-sluAccuracy (%)99.7—Unverified
5Wav2Vec2.0-ClassifierAccuracy (%)99.7—Unverified
6Finstreder (Quartznet + AMT)Accuracy (%)99.7—Unverified
7Wav2vec 2.0 SSLAccuracy (%)99.6—Unverified
8Finstreder (Conformer)Accuracy (%)99.5—Unverified
9AT-ATAccuracy (%)99.5—Unverified
10BERT, AC PretrainingAccuracy (%)99.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Finstreder (Conformer, character-based)Accuracy (%)89—Unverified
2Finstreder (Conformer)Accuracy (%)88—Unverified
3AT-ATAccuracy (%)84.9—Unverified
4Finstreder (Quartznet)Accuracy (%)84.8—Unverified
5SnipsAccuracy (%)84.2—Unverified
6GoogleAccuracy (%)79.3—Unverified
7Real + syntheticAccuracy (%)71.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Finstreder (Conformer, character-based)Accuracy-EN (%)87.9—Unverified
2Finstreder (Conformer)Accuracy-EN (%)80.4—Unverified
3Finstreder (Quartznet)Accuracy-EN (%)77.6—Unverified
4SnipsAccuracy-EN (%)68.7—Unverified
5GoogleAccuracy-EN (%)47.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ALBERTF1 score77.1—Unverified
2SpeechBERTF1 score71.75—Unverified
3QANet + GANF1 score63.11—Unverified
4BaselineF1 score58.71—Unverified
#ModelMetricClaimedVerifiedStatus
1Finstreder (Conformer)Accuracy (%)95.4—Unverified
2Finstreder (Quartznet)Accuracy (%)90—Unverified
3BaselineAccuracy (%)81.6—Unverified