|
--- |
|
license: cc-by-nc-sa-4.0 |
|
language: |
|
- en |
|
tags: |
|
- disfluency identification |
|
--- |
|
|
|
# Model Card for Model ID |
|
|
|
<!-- Provide a quick summary of what the model is/does. --> |
|
|
|
This BERT model classifies a dialogue system's user utterance as fluent or disfluent. |
|
|
|
## Model Details |
|
|
|
### Model Description |
|
|
|
<!-- Provide a longer summary of what this model is. --> |
|
|
|
|
|
|
|
- **Developed by:** 4i Intelligent Insights |
|
- **Model type:** BERT base cased |
|
- **Language(s) (NLP):** English |
|
- **License:** cc-by-nc-sa-4.0 |
|
|
|
### Model Sources |
|
|
|
<!-- Provide the basic links for the model. --> |
|
|
|
- **Repository:** http://research.4i.ai/code/BERT_disfluency_cls |
|
- **Paper:** https://aclanthology.org/2023.findings-acl.728/ |
|
|
|
## Uses |
|
|
|
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
|
|
|
The model is intended to be used for classifying English utterances of users interacting with a dialogue system. In our evaluation, the user utterances were speech transcriptions. |
|
|
|
|
|
## Out-of-Scope Use |
|
|
|
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
|
|
|
This model has not been evaluated to be used on machine-generated text. |
|
|
|
|
|
## Bias, Risks, and Limitations |
|
|
|
<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
|
|
|
This model may not be accurate with non-native English speakers. |
|
|
|
|
|
|
|
|
|
## Training Data |
|
|
|
<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
|
|
|
The model has been fine-tuned on the Fisher English Corpus: |
|
http://github.com/joshua-decoder/fisher-callhome-corpus |
