Authors: Gopalakrishnan (Intel Student Ambassador for oneAPI), Nikita Shiledarbaxi, Ugonna Chikezie
Emotion recognition has often been limited to analysing textual data in isolation, resulting in incomplete insights into the complexities of human emotions. Particularly in fields such as customer service, virtual assistance, and mental health support, we can significantly enhance human-machine interactions through emotionally intelligent systems, allowing for more personalized and empathetic communication, ultimately improving user satisfaction and engagement.
As an Intel® Student Ambassador, Gopalakrishnan developed a project called ‘Emotion Recognition using NLP’ leveraging Intel’s latest hardware and oneAPI-powered AI tools and frameworks on the Intel® Tiber™ Developer Cloud platform.
Problem Statement
The primary challenge/motivation behind the project was to design a system capable of accurately interpreting and analysing textual inputs using Intel’s hardware and oneAPI tools. Additionally, the aim was to ensure that the model maintains high performance across a range of hardware configurations, from resource-constrained edge devices to more robust high-performance systems.
Building The Solution Approach
In developing the Emotion Recognition model, the student ambassador focused on optimizing text-based emotion recognition using Intel® Distribution for Python and TensorFlow* Optimizations from Intel. By applying Natural Language Processing (NLP) techniques for text analysis, the model can detect emotional states from written text with high accuracy. Leveraging Intel-optimized Python libraries, the student ambassador ensured that the text processing pipeline is both efficient and scalable.
Intel’s oneAPI optimizations of AI libraries and frameworks helped significantly reduce computational time while enhancing the model’s predictive accuracy. Noteworthy performance improvements including a 25% reduction in model training time and 10% higher accuracy compared to traditional NLP approaches were achieved using oneAPI tools.
Learn more about the Emotion Recognition project:
• GitHub repository
• Demo video
Experience as an Intel Student Ambassador
Being as an Intel Student Ambassador has been an incredibly enlightening experience for Gopalkrishnan, filled with opportunities to explore and innovate within the realm of GenAI. Conducting several workshops on these cutting-edge topics has not only solidified his understanding but also enhanced his communication and teaching abilities. Initially, his primary interest was in ML, but Intel's advanced technologies and resources broadened his perspective, fostering a deep appreciation for CPU computing and its crucial role in optimizing machine learning processes.
The student ambassador cherishes an opportunity to connect with a diverse network of passionate individuals through the Intel Student Ambassador Program, who share a common vision for technological progress. The robust support from Intel has played a crucial role in shaping his academic journey and professional ambitions, encouraging a holistic perspective on technology's potential. This experience has been a remarkable journey of exploration and personal development, significantly influencing his career aspirations and deepening his commitment to the fields of AI and high-performance computing (HPC).
What's Next?
Moving forward, the student ambassador aims to expand the capabilities of the emotion recognition model to cover more nuanced emotions and incorporate more languages. Intel’s oneAPI programming paradigm can help him continue to optimize the system for diverse hardware architectures, allowing it to be deployed in various real-world scenarios such as telehealth, AI-driven customer service, and more. His future goal is to further refine the current model with an intent to assist industries in creating emotionally responsive and empathetic systems, contributing to more human-centred AI development.
We encourage you to jumpstart AI development with Intel’s state-of-the-art AI technologies. Sign up to Intel Tiber Developer Cloud today to develop, test, and deploy high-performance AI applications on the latest hardware including CPUs, GPUs, and other accelerators such as Intel® Gaudi® AI processors.
Useful Resources
Technical Software Product Marketing Engineer, Intel