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--- |
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license: cc-by-nc-sa-4.0 |
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language: |
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- en |
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tags: |
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- disfluency identification |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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This BERT model classifies a dialogue system's user utterance as fluent or disfluent. |
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## Model Details |
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### Model Description |
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- **Developed by:** 4i Intelligent Insights |
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- **Model type:** BERT base cased |
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- **Language(s) (NLP):** English |
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- **License:** cc-by-nc-sa-4.0 |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** To be announced |
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- **Paper:** To be announced |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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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. |
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## Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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This model has not been evaluated to be used on machine-generated text. |
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## Bias, Risks, and Limitations |
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This model may not be accurate with non-native English speakers. |
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## Training Data |
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<!-- 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. --> |
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The model has been fine-tuned on the Fisher English Corpus: |
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http://github.com/joshua-decoder/fisher-callhome-corpus |
