Infineon Technologies had 28 patents in artificial intelligence during Q1 2024. Infineon Technologies AG filed patents in Q1 2024 for systems, methods, and devices that detect audio signals, including wake words, using a combination of low power and high performance circuits. They also developed a method for detecting wake signals in audio data using machine learning models. Additionally, a microcontroller with a hardware power estimator circuit using a hardware artificial neural network was patented. Another patent involved a signature graph method for authenticating shared high-entropy data using easily identifiable graphs for human perception. GlobalData’s report on Infineon Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.

Infineon Technologies grant share with artificial intelligence as a theme is 32% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Systems, methods, and devices for wakeup word detection with continuous learning (Patent ID: US20240062755A1)

The patent filed by Infineon Technologies AG describes systems, methods, and devices for detecting audio signals, particularly wake words, using a combination of circuits and language processing models. The methods involve receiving an audio input, identifying a wake word using a first circuit, and determining if the identification process should be adjusted based on a designated accuracy threshold and the language processing model of a second circuit. The adjustment may involve modifying wake word detection operations based on the outcome of the determination.

The patent's claims detail the method steps and system configurations for implementing the audio signal detection process. These include adjusting power levels between circuits, determining accuracy thresholds for wake word identification, utilizing statistical distributions for threshold determination, updating language processing models based on identification operations, and adjusting weights associated with wake word identification. The system and device configurations involve audio front end circuits, processors for wake word identification, and learning modules for modifying identification processes based on accuracy thresholds and language processing models. Overall, the patent focuses on enhancing the accuracy and efficiency of audio signal detection through a combination of circuit operations and language processing techniques.

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