17957588. SYSTEM AND METHOD FOR A MODEL FOR PREDICTION OF SOUND PERCEPTION USING ACCELEROMETER DATA simplified abstract (Robert Bosch GmbH)

SYSTEM AND METHOD FOR A MODEL FOR PREDICTION OF SOUND PERCEPTION USING ACCELEROMETER DATA

Organization Name

Robert Bosch GmbH

Inventor(s)

Ivan Batalov of Pittsburgh PA (US)

Thomas Alber of Filderstadt (DE)

Filipe J. Cabrita Condessa of Pittsburgh PA (US)

Florian Lang of Karlsruhe (DE)

Felix Schorn of Renningen (DE)

Carine Au of Stuttgart (DE)

Matthias Huber of Saint-Petersburg (RU)

Dmitry Naumkin of Saint-Petersburg (RU)

Michael Kuka of Waiblingen (DE)

Balázs Lipcsik of Kistokaj (HU)

Martin Boschert of Stuttgart (DE)

Andreas Henke of Diemelstadt (DE)

SYSTEM AND METHOD FOR A MODEL FOR PREDICTION OF SOUND PERCEPTION USING ACCELEROMETER DATA - A simplified explanation of the abstract

This abstract first appeared for US patent application 17957588 titled 'SYSTEM AND METHOD FOR A MODEL FOR PREDICTION OF SOUND PERCEPTION USING ACCELEROMETER DATA

Simplified Explanation

The system described in the abstract utilizes machine learning to analyze sound and vibrational information to generate real-time sound perception scores.

• Processor programmed to receive sound and vibrational information
• Generate training data set using vibrational information and sound perception scores
• Feed training data set into un-trained machine learning model
• Output trained machine learning model after meeting convergence threshold
• Receive real-time vibrational information from device in second environment
• Output real-time sound perception score based on trained machine learning model

Potential Applications

This technology could be applied in various industries such as:

• Automotive industry for analyzing engine vibrations and sound perception
• Consumer electronics for improving sound quality in devices
• Healthcare for monitoring patient vitals through vibrations and sounds

Problems Solved

This technology helps in:

• Enhancing sound quality analysis in different environments
• Providing real-time feedback on sound characteristics
• Improving machine learning models for sound perception

Benefits

The benefits of this technology include:

• Increased accuracy in analyzing sound and vibrations
• Real-time monitoring and feedback on sound perception
• Enhanced performance of machine learning models

Potential Commercial Applications

The potential commercial applications of this technology could be seen in:

• Audio equipment manufacturing for quality control
• Environmental monitoring for detecting anomalies through sound and vibrations
• Industrial machinery maintenance for predictive analysis

Possible Prior Art

One possible prior art could be the use of machine learning models in analyzing sound perception scores in controlled environments.

How does this technology impact data privacy and security?

This article does not address the potential implications of collecting and analyzing sound and vibrational data in terms of data privacy and security.

What are the limitations of this technology in real-world applications?

The article does not discuss any limitations or challenges that may arise when implementing this technology in practical scenarios.

Original Abstract Submitted

A system includes a processor, wherein the processor is programmed to receive sound information and vibrational information from a device in a first environment, generate a training data set utilizing at least the vibrational information and a sound perception score associated with the corresponding sound of the vibrational information, wherein the training data set is fed into an un-trained machine learning model, in response to meeting a convergence threshold of the un-trained machine learning model, outputting a trained machine learning model, receive real-time vibrational information from the device in a second environment, and based on the real-time vibrational information as an input to the trained machine learning model, output a real-time sound perception score indicating characteristics associated with sound emitted from the device.