Dialog Act Classification
11 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Dialog Act Classification
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
CPED
SILICONE Benchmark
Latest papers with no code
SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks
In this work, we introduce several new annotated SLU benchmark tasks based on freely available speech data, which complement existing benchmarks and address gaps in the SLU evaluation landscape.
A Universality-Individuality Integration Model for Dialog Act Classification
Experiments were made over two most popular benchmark data sets SwDA and MRDA for dialogue act classification, and the results show that extracting the universalities and individualities between cues can more fully excavate the hidden information in the utterance, and improve the accuracy of automatic dialogue act recognition.
Annotation Process for the Dialog Act Classification of a Taglish E-commerce Q\&A Corpus
The SWBD-DAMSL tagset for DA classification was modified to 28 tags fitting the categories applicable to e-commerce conversations.
Multi-level Gated Recurrent Neural Network for Dialog Act Classification
In this paper we focus on the problem of dialog act (DA) labelling.
Context-aware Neural-based Dialog Act Classification on Automatically Generated Transcriptions
This paper presents our latest investigations on dialog act (DA) classification on automatically generated transcriptions.
Lexico-acoustic Neural-based Models for Dialog Act Classification
We propose a neural model that processes both lexical and acoustic features for classification.
Using Context Information for Dialog Act Classification in DNN Framework
Previous work on dialog act (DA) classification has investigated different methods, such as hidden Markov models, maximum entropy, conditional random fields, graphical models, and support vector machines.
Neural-based Context Representation Learning for Dialog Act Classification
We explore context representation learning methods in neural-based models for dialog act classification.
