Emotion-driven music creation system using ai and biometric data

Abstract

An Al-powered system designed to dynamically generate music tailored to users' emotional needs by analyzing vital signs collected via a smartphone app and data from social media history. The system utilizes advanced algorithms to assess users' current emotional states and create music that aligns with those states. This innovative approach bridges the gap between digital technology and emotional well-being, offering a novel solution for personalized music therapy, mental health support, and enhanced music experiences. This invention introduces an Al-powered system designed to analyze musical compositions and generate linguistically related content. Leveraging sophisticated algorithms, the system deciphers musical chords and harmonies, transforming these auditory elements into descriptive words and sentences. This process reflects both the conceptual and emotional nuances of the music.

Description

[0001] Emotion-Driven Music Creation System Using Al and Biometric Data

[0002] Introduction: This invention pertains to an Al-powered system that generates personalized music tailored to users' emotional needs by analyzing vital signs collected via a smartphone app and data from social media history. The system uses advanced algorithms to assess the users' current emotional states and create music that aligns with those states, offering a novel approach to personalized music therapy and mental health support.

[0003] System Components:

[0004] Data Collection Modules: Collect real-time data from users' smartphones, including heart rate, blood pressure, activity levels, and social media activity. Users must grant permission to collect this data by installing the associated app.

[0005] Analysis Engine: Employs machine learning algorithms to process the collected data, identifying emotional states and preferences.

[0006] Music Generation Module: Uses Al to create music that matches the emotional cues derived from the analysis.

[0007] User Interface: An interactive platform that allows users to provide feedback, which is used to refine future music generation.

[0008] Data Processing:

[0009] Vital Signs Analysis: The system analyzes heart rate variability, sleep patterns, and activity levels to assess the user's emotional and physical states.

[0010] Social Media Analysis: Text mining and sentiment analysis are performed on the user’s social media history to gauge mood and emotional trends. Music Composition: The system generates music by analyzing the emotional output from the previous modules, aiming to either enhance or modulate the user's mood.

[0011] Privacy and Security Considerations: The system implements robust data encryption and anonymization techniques to protect user data, ensuring compliance with data privacy regulations like GDPR.

[0012] Field of the Invention: The present invention relates to artificial intelligence applications in music and language analysis, specifically aimed at controlling and healing unconscious emotional feelings through advanced Al algorithms.

[0013] Background of the Invention: Current therapeutic approaches often lack the integration of Al for precise emotional analysis and feedback.

[0014] Traditional methods do not effectively address the unconscious emotional triggers that can be influenced by music and language.

[0015] Summary of the Invention: The invention provides a novel system that utilizes Al for the analysis of music and language to identify emotional triggers and deliver therapeutic feedback. The system includes modules for music analysis, language processing, and a feedback mechanism to help users manage and heal unconscious emotional feelings.

[0016] Detailed Description of the Invention:

[0017] System Components:

[0018] Data Collection Modules: The system gathers real-time data from users’ smartphones, tracking vital signs such as heart rate, blood pressure, and activity levels. It also analyzes social media interactions, with users consenting to this data collection via an app. This component is designed to be highly sensitive, capturing subtle physiological shifts that might indicate changes in the user’s emotional state. By also considering the user’s music history, the system builds a comprehensive emotional profile.

[0019] Analysis Engine: At the heart of the system lies the analysis engine, which uses machine learning to process collected data. This engine can detect and classify the user’s emotional states with high accuracy, drawing on patterns from biometric and social media data. The system doesn’t just react to the present; it anticipates emotional shifts by learning from past data, making it a truly proactive tool for emotional regulation.

[0020] Music Generation Module: Using Al, this module crafts music that resonates with the emotional cues identified by the analysis engine. The system can either select existing tracks that match the user’s emotional needs or create entirely new compositions. By adjusting elements such as tempo, key, and instrumentation in real-time, the system ensures the music remains emotionally aligned with the user’s state.

[0021] Language Processing Module: Complementary to the music, this module interprets the emotional content of the user’s social media activity. It generates personalized language responses that offer support or guidance, whether through text or voice. This could include sending comforting messages or suggesting mindfulness practices tailored to the user’s current mood.

[0022] User Interface: The interface is designed to be user-friendly, allowing individuals to provide feedback and adjust the system’s settings. It also features tools for users to track their emotional progress, offering insights into how their moods have changed over time and how the system’s interventions have helped.

[0023] Data Processing:

[0024] Vital Signs Analysis: The system examines vital signs such as heart rate variability and sleep patterns to gauge the user’s physical and emotional states. This analysis is integrated with social media data, providing a comprehensive view of the user’s emotional well-being. The system’s predictive capabilities also allow it to detect early signs of stress or distress, enabling timely interventions.

[0025] Social Media Analysis: Through text mining and sentiment analysis, the system evaluates the emotional content of the user’s social media interactions. By identifying patterns and correlating these with biometric data, the system can deliver more accurate and personalized interventions.

[0026] Music Composition: Based on the emotional output from the analysis modules, the system generates music aimed at enhancing or modulating the user’s mood. The music is carefully crafted to match the user’s current emotional needs, offering a more tailored therapeutic experience.

[0027] Use Cases:

[0028] Mental Health Applications: This system is particularly useful in therapeutic settings, where it can support individuals dealing with anxiety, depression, or other emotional challenges. By generating personalized music and language interventions, the system offers an innovative tool for both therapists and patients.

[0029] Personalized Entertainment: Integrated into music streaming services, the system can provide users with playlists that adapt to their emotional needs in real-time, enhancing the overall listening experience.

[0030] Educational Tools: The system can also serve as a powerful educational resource, teaching users about music theory, emotional intelligence, and language processing through interactive experiences.

[0031] Comparative Analysis:

[0032] Unlike static music therapy tools, this system offers a dynamic, adaptive solution that evolves in response to real-time data. The integration of biometric feedback ensures that interventions are always aligned with the user’s current emotional state, setting it apart from traditional approaches. Additionally, the system’s ability to generate new music compositions tailored to the user’s needs is a significant innovation. Expected Outcomes:

[0033] Improved Emotional Regulation: Users will experience better emotional regulation through the system’s personalized interventions.

[0034] Enhanced Therapeutic Outcomes: Therapists can use the system to complement traditional therapeutic approaches, particularly in treating emotional disorders.

[0035] Wider Accessibility: The digital platform ensures that therapeutic interventions are accessible to a broader audience, including those who may not have access to traditional therapy.

[0036] Privacy and Security Considerations: The system is designed with privacy in mind, utilizing robust data encryption and anonymization techniques to protect user data. It complies with all relevant data privacy regulations, such as GDPR, and gives users complete control over their data, including the option to opt-out at any time.

[0037] Conclusion: This invention represents a major advancement in the field of Al-driven emotional therapy. By combining real-time data analysis, personalized music generation, and empathetic language processing, the system offers a comprehensive tool for emotional regulation. Its ability to adapt to the user’s needs in real-time makes it a powerful resource for both personal use and professional therapy.

Claims

AMENDED CLAIMS received by the International Bureau on 12 September 2025 (12.09.2025)Claims

1. . A computer-implemented system for generating personalized music or sound experiences, comprising:- one or more processors;- a memory storing instructions that, when executed by the processors, cause the system to:- collect user-related data from digital cultural activity, including social media interactions and online behavior;- integrate astrological parameters including planetary positions and cycles;- generate a cultural-astrological profile of the user; and- produce personalized music or sound experiences adapted to said profile.

2. . The system of claim 1 , wherein social media interactions comprise at least one of: user posts, likes, shares, or cultural references.

3. . The system of claim 1 , wherein astrological parameters include user-specific birth chart data combined with real-time planetary cycles.

4. . The system of claim 1 , wherein the generated sound experiences are selected from:- culturally significant music archives,- Al-generated compositions, or- hybrid formats combining both.

5. . The system of claim 1 , wherein personalization emphasizes alignment with cultural identity and astrological timing rather than physiological states.

6. . The system of claim 2, wherein cultural references are detected through hashtags, idioms, symbolic language, or other markers of cultural identity.

7. . The system of claim 3, wherein astrological timing synchronizes music recommendations with planetary transits relevant to the user.

8. . The system of claim 1 , wherein the output evolves dynamically as cultural trends and astrological conditions change over time.

9. . The system of claim 1 , wherein user feedback refines future outputs to strengthen cultural and astrological resonance.

10. . The system of claim 4, wherein Al-generated compositions use generative algorithms trained on culturally diverse datasets.

11. . The system of claim 1 , wherein outputs can be adapted for applications in meditation, cultural education, entertainment, or identity expression.

12. . The system of claim 1 , wherein recommendations exclude biometric data and focus exclusively on contextual digital and astrological inputs.

13. . The system of claim 1 , wherein a weighted algorithm balances digital cultural behavior with astrological cycles to define user profiles.

14. . The system of claim 1 , wherein the platform delivers real-time updates through a web or mobile application.

15. . The system of claim 1 , further comprising a cloud-based architecture enabling scalable personalization across diverse cultural and astrological datasets.

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