Detecting sentiments is one of the most important marketing strategies in today’s world. we could personalize different things for an individual specifically to suit their interest. Getting the sentiment of the customers will improve the outcome of the products. Normally sentiment analysis is done through the text data, But we have a lot of unused audio data. For this reason, we decided to do make a processor where it could detect a person’s emotions just by their voice which will let us manage many AI-related applications. Some examples could be including call centres to play music when one is angry…
Named-entity recognition is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages,etc.,
Link to Code: https://github.com/Vijayvj1/Custom_NER_Spacy3
Check the spaCy Version
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML covers the complete pipeline from the raw dataset to the deployable machine learning model. AutoML was proposed as an artificial intelligence-based solution to the ever-growing challenge of applying machine learning. The high degree of automation in AutoML allows non-experts to make use of machine learning models and techniques without requiring them to become experts in machine learning. Automating the process of applying machine learning end-to-end additionally offers the advantages of producing simpler solutions, faster creation of those solutions, and models that…
As a subset of artificial intelligence, deep learning lies at the heart of various innovations: self-driving cars, natural language processing, image recognition and so on.
One of the biggest challanges in Automatic Speech Recognition is the preparation and augmentation of audio data. Audio data analysis could be in time or frequency domain, which adds additional complex compared with other data sources such as images and text.
What is Augmentation ?
Deep neural networks achieved state of the art performances in many artificial intelligence fields, like image classification , object detection and audio classification. However, they usually need a very large amount of labelled data to obtain good results and these data might not be available due to high labelling costs or due to the scarcity…
Imbalanced datasets is relevant primarily in the context of supervised machine learning involving two or more classes.
Imbalance means that the number of data points available for different the classes is different:
If there are two classes, then balanced data would mean 50% points for each of the class.
For most machine learning techniques, little imbalance is not a problem. So, if there are 60% points for one class and 40% for the other class, it should not cause any significant performance degradation.
Only when the class imbalance is high, e.g. 90% points for one class and 10% for the…
Deep Learning Engineer - Machine Learning Engineer - Audio Engineer