SOTAVerified

Spoken Language Understanding

Papers

Showing 101–125 of 550 papers

TitleStatusHype
End-to-end spoken language understanding using joint CTC loss and self-supervised, pretrained acoustic encoders—0
The Pipeline System of ASR and NLU with MLM-based Data Augmentation toward STOP Low-resource Challenge—0
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge—0
Joint Modelling of Spoken Language Understanding Tasks with Integrated Dialog History—0
Non-autoregressive End-to-end Approaches for Joint Automatic Speech Recognition and Spoken Language Understanding—0
A Preliminary Evaluation of ChatGPT for Zero-shot Dialogue Understanding—0
A Deep Learning System for Domain-specific Speech Recognition—0
Improving the Intent Classification accuracy in Noisy Environment—0
Adaptive Knowledge Distillation between Text and Speech Pre-trained Models—0
SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks—0
Fillers in Spoken Language Understanding: Computational and Psycholinguistic Perspectives—0
HIT-SCIR at MMNLU-22: Consistency Regularization for Multilingual Spoken Language UnderstandingCode0
Skit-S2I: An Indian Accented Speech to Intent datasetCode1
Spoken Language Understanding for Conversational AI: Recent Advances and Future Direction—0
SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks—0
A Robust Semantic Frame Parsing Pipeline on a New Complex Twitter Dataset—0
Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasksCode0
Bidirectional Representations for Low Resource Spoken Language Understanding—0
Multitask Learning for Low Resource Spoken Language Understanding—0
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding—0
Introducing Semantics into Speech Encoders—0
An Investigation of the Combination of Rehearsal and Knowledge Distillation in Continual Learning for Spoken Language UnderstandingCode0
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding—0
Comparative layer-wise analysis of self-supervised speech modelsCode1
Robust Unstructured Knowledge Access in Conversational Dialogue with ASR ErrorsCode0
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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