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@article{159254,
        author = {Solunke Akash and Akash Sahani and Shivam Singh and Mohit Sancheti},
        title = {Speech Emotion Recognition using CNN},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {11},
        pages = {1219-1222},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159254},
        abstract = {Speech Emotion Recognition (SER) is an advanced technology that automatically obtains the emotional countries of speakers by assaying their speech signals. It's a collection of colourful methodologies and algorithms that process and classify speech signals to descry feelings bedded in them. SER takes speech as the carrier of emotion to study the conformation and change of colourful feelings in speech. This enables computers to dissect the speaker's specific emotional situation through speech, making mortal- computer commerce more humanized and intuitive. To enhance the delicacy of an intelligent SER system, a speech emotion recognition model grounded on the point representation of a Convolutional Neural Network (CNN) can be used. CNNs are a type of neural network that can effectively dissect and classify image data, making them well- suited for use in SER systems that reuse speech signals as image- suchlike representations. },
        keywords = {},
        month = {},
        }