I have textual data, I need to annotate for further experiments but I do not have sufficient domain expertise to label it myself or financial resource to hire annotators. Is there any other method like standard machine learning/deep learning approach to annotate the data. The data is on sentiment analysis and I need to classify this data into three classes based in the sentiment. I will be using this annotated data for further deep learning architectures. Is there a way other manual annotation or hiring annotators.The data is contains Indian language
Have a look at https://appen.com/blog/data-annotation/Chapter Machine Learning Methods in Automatic Image Annotation
Conference Paper Using Machine Learning Techniques to Reduce Data Annotation Time
You can use generative adversarial networks for this purpose.
Have a look at https://appen.com/blog/data-annotation/Chapter Machine Learning Methods in Automatic Image Annotation
Conference Paper Using Machine Learning Techniques to Reduce Data Annotation Time
Hi Ravi,
There are various mechanisms you can explore for automated data annotation using transfer learning concepts. I would suggest you to train a Multilingual BERT based sentiment model with a lot of languages and then use your dataset as a test set. This will give u decent sentiment labeling if the language is one of the languages in the trainset. In case u wish to use this data for training, you would need to go through the outputs of the automated labeling process.
Also if you could share the particular Indian language you are working with, I can help you with more details.
Hope this helps!
Thanks
Anupama
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