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Spoken Language Understanding

Papers

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Showing 301–350 of 550 papers

TitleStatusHype
Worldly Wise (WoW) - Cross-Lingual Knowledge Fusion for Fact-based Visual Spoken-Question Answering—0
Generalized zero-shot audio-to-intent classification—0
Generative Context-aware Fine-tuning of Self-supervised Speech Models—0
Global-Locally Self-Attentive Encoder for Dialogue State Tracking—0
Graph-based alignment of narratives for automated neurological assessment—0
Graph Databases for Designing High-Performance Speech Recognition Grammars—0
Hallucination of speech recognition errors with sequence to sequence learning—0
HAN: Higher-order Attention Network for Spoken Language Understanding—0
HC^2L: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding—0
Hello, Who is Calling?: Can Words Reveal the Social Nature of Conversations?—0
HRItk: The Human-Robot Interaction ToolKit Rapid Development of Speech-Centric Interactive Systems in ROS—0
Human Evaluation of Conceptual Route Graphs for Interpreting Spoken Route Descriptions—0
Human-Machine Dialogue as a Stochastic Game—0
Hybrid Attention based Multimodal Network for Spoken Language Classification—0
Hybrid Dialog State Tracker with ASR Features—0
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks—0
Hyper-parameter Optimisation of Gaussian Process Reinforcement Learning for Statistical Dialogue Management—0
I^2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understanding—0
IBM's Belief Tracker: Results On Dialog State Tracking Challenge Datasets—0
Identifying Domain Independent Update Intents in Task Based Dialogs—0
Impact Analysis of the Use of Speech and Language Models Pretrained by Self-Supersivion for Spoken Language Understanding—0
Improving End-to-End Models for Set Prediction in Spoken Language Understanding—0
Improving End-to-End Speech Processing by Efficient Text Data Utilization with Latent Synthesis—0
Improving End-to-End Speech-to-Intent Classification with Reptile—0
Improving Recurrent Neural Networks For Sequence Labelling—0
Improving Slot Filling by Utilizing Contextual Information—0
Improving Speaker Diarization using Semantic Information: Joint Pairwise Constraints Propagation—0
Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses—0
Improving Spoken Language Understanding by Wisdom of Crowds—0
Improving Textless Spoken Language Understanding with Discrete Units as Intermediate Target—0
Improving the Intent Classification accuracy in Noisy Environment—0
Improving Transducer-Based Spoken Language Understanding with Self-Conditioned CTC and Knowledge Transfer—0
Increasing faithfulness in human-human dialog summarization with Spoken Language Understanding tasks—0
RNN based Incremental Online Spoken Language Understanding—0
Incremental processing of noisy user utterances in the spoken language understanding task—0
Incremental Segmentation and Decoding Strategies for Simultaneous Translation—0
Inducing Global and Local Knowledge Attention in Multi-turn Dialog Understanding—0
Information Navigation System Based on POMDP that Tracks User Focus—0
Injecting Lexical Contrast into Word Vectors by Guiding Vector Space Specialisation—0
Inspecting Spoken Language Understanding from Kids for Basic Math Learning at Home—0
Integrating Dialog History into End-to-End Spoken Language Understanding Systems—0
Integrating Incremental Speech Recognition and POMDP-Based Dialogue Systems—0
Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understanding—0
Integrating Self-supervised Speech Model with Pseudo Word-level Targets from Visually-grounded Speech Model—0
Integration of Pre-trained Networks with Continuous Token Interface for End-to-End Spoken Language Understanding—0
Intent Classification Using Pre-trained Language Agnostic Embeddings For Low Resource Languages—0
Intent Recognition and Unsupervised Slot Identification for Low Resourced Spoken Dialog Systems—0
Interpreting Situated Dialogue Utterances: an Update Model that Uses Speech, Gaze, and Gesture Information—0
Interventional Speech Noise Injection for ASR Generalizable Spoken Language Understanding—0
Introducing Semantics into Speech Encoders—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Finstreder (Conformer + AMT, character-based)Accuracy (%)99.8—Unverified
2UniverSLUAccuracy (%)99.8—Unverified
3Finstreder (Quartznet + AMT)Accuracy (%)99.7—Unverified
4textual-kd-sluAccuracy (%)99.7—Unverified
5Wav2Vec2.0-ClassifierAccuracy (%)99.7—Unverified
6E2E SLP two-stepAccuracy (%)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