Dialogue Act Classification On Icsi Meeting
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| Pretrained Hierarchical Transformer | 92.4 | Hierarchical Pre-training for Sequence Labelling in Spoken Dialog | - |
| HGRU + Beam Search + Guided attention | 91.6 | Guiding attention in Sequence-to-sequence models for Dialogue Act prediction | |
| Speaker | 91.4 | Speaker Turn Modeling for Dialogue Act Classification | |
| Bi-RNN + Self-Attention + Context | 91.1 | Dialogue Act Classification with Context-Aware Self-Attention | |
| CRF-ASN | 91.7 | Dialogue Act Recognition via CRF-Attentive Structured Network | - |
| Bi-LSTM-CRF | 90.9 | Dialogue Act Sequence Labeling using Hierarchical encoder with CRF | |
| Hierarchical Fusion | 91.8 | Hierarchical Fusion for Online Multimodal Dialog Act Classification | |
| SGNN | 86.7 | Self-Governing Neural Networks for On-Device Short Text Classification | - |
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