Word recognition using deep learning is a simple approach to speech recognition in general. From this word-level recognition, the emotional expression recognition model. The emotion recognition model can be used to describe the important level of action on future planned hardware implementation. This research was conducted using MFCC as the feature extraction method from the audio data and using the CNN-LSTM approach for the emotional expression classifier. The model itself will be implemented into a humanoid robot to become a companion robot for the elderly. The model itself has 67% accuracy for emotion recognition and 97% accuracy for word recognition. However, the model only attained 20% accuracy in real-life testing using the humanoid robot as the model tends to overfitting as a result of the lack of data used in model training.
pada jaman modern ini, teknologi semakin canggih dan bisa digunakan oleh siapa saja, contohnya adalah lockpicking yang alatnya dapat dibeli oleh siapa saja dan mudah untuk dipelajari. Oleh karena itu, kunci fisik semakin kuno dan mudah untuk dibobol oleh siapa saja. Dengan menerapkan sistem passive keyless entry yang sudah diterapkan pada mobil jaman sekarang, menambah keamanan dan kenyamanan dari pengguna mobil tersebut. sistem itu kita coba terapkan pada ESP32 dan membuat kunci digital walaupun pada penilitian ini masih kurang pada sistem keamanan kartu menggunakan digital signature algorithm, sistem passive keyless entry berjalan dengan sesuai harapan dengan menggunakan RFID sebagai input pengenal dari UID masing – masing kartu RFID yang dianggap unik dan mudah untuk digunakan.
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