Google LLC (20240304187). SELECTIVE ADAPTATION AND UTILIZATION OF NOISE REDUCTION TECHNIQUE IN INVOCATION PHRASE DETECTION simplified abstract
Contents
SELECTIVE ADAPTATION AND UTILIZATION OF NOISE REDUCTION TECHNIQUE IN INVOCATION PHRASE DETECTION
Organization Name
Inventor(s)
Christopher Hughes of Redwood City CA (US)
Yiteng Huang of Basking Ridge NJ (US)
Turaj Zakizadeh Shabestary of San Francisco CA (US)
Taylor Applebaum of Mountain View CA (US)
SELECTIVE ADAPTATION AND UTILIZATION OF NOISE REDUCTION TECHNIQUE IN INVOCATION PHRASE DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240304187 titled 'SELECTIVE ADAPTATION AND UTILIZATION OF NOISE REDUCTION TECHNIQUE IN INVOCATION PHRASE DETECTION
The patent application describes techniques for selectively adapting and utilizing noise reduction in detecting features of audio data frames, such as an invocation phrase or voice characteristics for speaker identification. These techniques enhance the accuracy of feature detection in various audio environments, including those with high background noise levels. The innovations can be integrated with automated assistants to adjust their functionality based on the detected features.
- Selective adaptation and utilization of noise reduction techniques in detecting features of audio data frames
- Improved accuracy and robustness in detecting features like invocation phrases and voice characteristics
- Integration with automated assistants to enhance functionality based on detected features
- Effective in noisy audio environments
- Enhances speaker identification and other audio analysis tasks
Potential Applications: - Speech recognition systems - Speaker identification technologies - Automated assistants and voice-controlled devices - Audio processing software
Problems Solved: - Enhancing accuracy in detecting features in noisy audio environments - Improving speaker identification and voice analysis tasks - Adapting automated assistants based on detected audio features
Benefits: - Increased accuracy and robustness in feature detection - Enhanced performance in noisy audio environments - Improved functionality of automated assistants based on audio analysis
Commercial Applications: Title: Enhanced Audio Feature Detection Technology for Automated Assistants This technology can be utilized in various commercial applications, including speech recognition systems, speaker identification technologies, and automated assistants. The market implications include improved user experience, enhanced functionality, and increased efficiency in audio processing tasks.
Prior Art: Prior art related to this technology may include research on noise reduction techniques in audio processing, speaker identification algorithms, and automated assistants' adaptation based on audio features.
Frequently Updated Research: Researchers are continuously exploring new methods to enhance feature detection in audio data frames, improve noise reduction algorithms, and optimize automated assistants' functionality based on audio analysis.
Questions about the Technology: 1. How does this technology improve the accuracy of feature detection in noisy audio environments? 2. What are the potential applications of integrating these techniques with automated assistants?
Original Abstract Submitted
techniques are described for selectively adapting and/or selectively utilizing a noise reduction technique in detection of one or more features of a stream of audio data frames. for example, various techniques are directed to selectively adapting and/or utilizing a noise reduction technique in detection of an invocation phrase in a stream of audio data frames, detection of voice characteristics in a stream of audio data frames (e.g., for speaker identification), etc. utilization of described techniques can result in more robust and/or more accurate detections of features of a stream of audio data frames in various situations, such as in environments with strong background noise. in various implementations, described techniques are implemented in combination with an automated assistant, and feature(s) detected utilizing techniques described herein are utilized to adapt the functionality of the automated assistant.
