Emotion Recognition using Speech

In this project, our focus is on emotion recognition using speech as part of an online psychological counseling program. We have undertaken various responsibilities to ensure the success of this endeavor. Our primary role involves data acquisition and preparation. We collect relevant speech data from participants, ensuring the ethical handling of sensitive information. Subsequently, we perform crucial tasks such as data cleaning, feature selection, and preprocessing. This includes transforming, scaling, and normalizing the data to prepare it for analysis.

Python programming language, along with relevant packages and libraries, serves as our primary toolset for implementing the project. Leveraging the capabilities of Python, we apply analytical techniques to address classification, regression, and clustering problems related to emotion recognition. These techniques enable us to extract valuable insights from the speech data and accurately classify different emotional states. Throughout the project, we prioritize providing comprehensive reports that highlight our findings and analysis. These reports serve as a guide for decision-making, helping professionals in the online psychological counseling program make informed choices to enhance the effectiveness of their interventions.

By working on emotion recognition using speech, we aim to contribute to the advancement of psychological counseling programs. Our efforts in data acquisition, data preparation, and applying analytical techniques demonstrate our commitment to improving the quality of care and support provided to individuals seeking online counseling services.