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svm-model

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The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datasets, including Convolutional Neural Network (CNN).

  • Updated Oct 30, 2019
  • Python
wmburke
wmburke commented Jun 25, 2017

the search box should except advanced search capabilities, eg adding a - before a word should black list it from the search

This should be common functionality for our search engine, we just need to be able to pass it on - then we can include advanced search instructions as well.

In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity for their ability to perform well without any input hand-crafted features. Speech emotion on sets obtained from RAVDESS corpus is classified using a conventionally used Support Vector Machine (SVM) and its performance is compared to that of a bidirectional long short-term memory (LSTM).

  • Updated Jul 11, 2019
  • Jupyter Notebook

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