Text-Based Song Generation System with Automatic Emotion Extraction
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Solution Overview
Problem
Existing song generation systems require users to manually set various parameters such as emotion, rhythm, music style, and instrument, which is difficult and time-consuming, especially for those without music knowledge.
Innovation Solution
A method and apparatus that automatically generate songs using text input, extracting topics and emotions to determine melodies and generate lyrics, allowing users to create songs through simple operations without manual parameter setting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually set parameters such as emotion, rhythm, music style, and instrument, then the song generation can be customized, but the operation becomes difficult and time-consuming
Solution Approach 1:
The patent introduces an intermediary mechanism that automatically extracts features from text input and converts them into music parameters. The system uses a text processing module to extract semantic features and an emotion recognition module to identify emotional tones, then automatically maps these to musical parameters like rhythm, instrument selection, and melody, eliminating the need for users to manually configure these settings
Solution Approach 2:
The patent replaces the manual mechanical process of parameter setting with an automated computational system. Instead of users manually selecting and adjusting multiple music parameters, the system uses automated algorithms including machine learning models and natural language processing to generate all necessary music parameters from text input, significantly reducing operational complexity
2Manufacturing precision
If users manually set various music parameters, then the song generation can be precise, but it requires music knowledge which most users do not have
Solution Approach 1:
The patent employs an intermediary translation layer that converts user-friendly text descriptions into precise music parameters. The text processing module extracts semantic meaning from simple user inputs, and the emotion recognition module translates emotional descriptors into specific musical characteristics, automatically generating precise songs without requiring users to understand or specify complex music theory concepts
Solution Approach 2:
The patent changes the parameter space from complex music theory parameters to simple text-based semantic features. Instead of requiring users to specify precise musical parameters like tempo in BPM, key signatures, or instrument specifications, the system accepts high-level text descriptions and automatically transforms them into the appropriate musical parameters through learned mappings from training data
3Productivity
If the system automatically processes text input to generate songs, then the process becomes quick and simple, but the customization control is reduced
Solution Approach 1:
The patent implements a dynamic control mechanism where the degree of automation can be adjusted based on user needs. The system allows users to provide simple text prompts for rapid generation, or to iteratively refine results by providing feedback on specific aspects like melody or instrumentation, enabling a spectrum from fully automated to more controlled generation modes
Data Source
AI summary
The disclosure provides a method and an apparatus for song generation. A text input may be received. A topic and an emotion may be extracted from the text input. A melody may be determined according to the topic and the emotion. Lyrics may be generated according to the melody and the text input. A song may be generated at least according to the melody and the lyrics.