18649278. ACOUSTIC NEURAL NETWORK SCENE DETECTION simplified abstract (Snap Inc.)
Contents
ACOUSTIC NEURAL NETWORK SCENE DETECTION
Organization Name
Inventor(s)
Jinxi Guo of Los Angeles CA (US)
Jia Li of Marina Del Rey CA (US)
ACOUSTIC NEURAL NETWORK SCENE DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18649278 titled 'ACOUSTIC NEURAL NETWORK SCENE DETECTION
- Simplified Explanation:**
The patent application describes an acoustic environment identification system that utilizes neural networks to accurately identify different environments based on audio data.
- Key Features and Innovation:**
- Uses convolutional neural networks to generate audio feature data.
- Utilizes a recursive neural network to process the audio feature data and generate characterization data.
- Modifies the characterization data using a weighting system for signature data items.
- Employs classification neural networks to classify different environments.
- Potential Applications:**
This technology can be used in:
- Smart home systems for automatically adjusting settings based on the identified environment.
- Security systems to detect unauthorized access based on environmental sounds.
- Industrial settings for monitoring and optimizing environmental conditions.
- Problems Solved:**
- Accurately identifying different acoustic environments.
- Automating the process of environment classification.
- Enhancing the capabilities of audio-based systems.
- Benefits:**
- Improved efficiency in environment identification.
- Enhanced security measures through accurate classification.
- Increased automation in various applications.
- Commercial Applications:**
- "Acoustic Environment Identification System for Smart Homes and Security Systems"
- Prior Art:**
Further research can be conducted in the field of acoustic environment identification systems, neural networks, and audio processing technologies to explore prior art related to this innovation.
- Frequently Updated Research:**
Stay updated on advancements in neural network technology, audio processing algorithms, and environmental sensing techniques to enhance the capabilities of the acoustic environment identification system.
- Questions about Acoustic Environment Identification Systems:**
1. How can this technology benefit the field of smart home automation? 2. What are the potential challenges in implementing this system in industrial settings?
Original Abstract Submitted
An acoustic environment identification system is disclosed that can use neural networks to accurately identify environments. The acoustic environment identification system can use one or more convolutional neural networks to generate audio feature data. A recursive neural network can process the audio feature data to generate characterization data. The characterization data can be modified using a weighting system that weights signature data items. Classification neural networks can be used to generate a classification of an environment.
