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Analysed syntax and Semantics of Corpus of Text Documents Retrieved from Web Scraping of News articles from Inshorts and followed the Standard NLP Workflow of the CRISP-DM model.
Python wrapper for GENIA tagger
Audio is sent to DEEP-LEARNING 7-LAYERED DNN Model , which considers spectrogram of the audio and uses the Librosa library for classifying the particular emotions Angry, Sad, Disgust, Surprised, and a testing accuracy of 75%. The calls are classified based on following features in our DL Model: ### MelSpectrogram, MFCC, Spectral-Contrast, Chroma,Tonnetz The text is prioritized using TF-IDF, Page Ranking, Cosine Similarity using steps:
Classification dataset generator library for high level Nlp tasks
Classification dataset generator library for high level Nlp tasks
Introduction to part-of-speech tagging and shallow parsing with keras
Shallow Parsing Annotation Interface and Algorithms