AI Technology Stack

Our technology analyzes individual cardiac and breathing rhythms and selects music based on key attributes like tempo, key, scale, and structure.Our SaaS platform connects wearables and music providers, to deliver a playlist that affects and optimizes pertinent biomarkers in a measurable manner, boosting music’s proven benefits.We use DNN (Deep Neural Networks) to identify and cluster different musical attributes, as well as HRV (Heart Rate Variability) vectors in large scale, to quantify music’s effect. Based on proprietary analysis method, we determine a scientific match between music and biomarkers, and generate insights for personal music recommendation.
Audio and Speech Processing, Deep Learning, Machine Learning
1
Semi-Supervised Learning, Supervised Learning, Unsupervised Learning
Convolutional Neural Network (CNN), Deep Neural Networks (DNN), LSTM, Random Forest, Recurrent Neural Network (RNN)
Amazon Web Services
Keras, Scikit-Learn, TensorFlow
Python
CPU, GPU
Cloud

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