Samsung electronics co., ltd. (20240119925). SYSTEM AND METHOD FOR POST-ASR FALSE WAKE-UP SUPPRESSION simplified abstract
Contents
- 1 SYSTEM AND METHOD FOR POST-ASR FALSE WAKE-UP SUPPRESSION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEM AND METHOD FOR POST-ASR FALSE WAKE-UP SUPPRESSION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SYSTEM AND METHOD FOR POST-ASR FALSE WAKE-UP SUPPRESSION
Organization Name
Inventor(s)
Tapas Kanungo of Redmond WA (US)
Preeti Saraswat of Santa Clara CA (US)
Stephen Michael Walsh of Sunnyvale CA (US)
SYSTEM AND METHOD FOR POST-ASR FALSE WAKE-UP SUPPRESSION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240119925 titled 'SYSTEM AND METHOD FOR POST-ASR FALSE WAKE-UP SUPPRESSION
Simplified Explanation
The method described in the patent application involves using machine learning models to predict the likelihood of a wake word or phrase being spoken in a speech signal, and taking actions based on those predictions.
- Obtaining a speech signal
- Predicting the likelihood of a wake word or phrase using a machine learning model
- Performing automatic speech recognition if the likelihood exceeds a threshold
- Predicting the likelihood of the wake word or phrase using a second machine learning model
- Generating instructions to perform an action based on the second likelihood exceeding a threshold
Potential Applications
This technology could be applied in smart speakers, virtual assistants, and other voice-controlled devices to improve wake word detection and response accuracy.
Problems Solved
This technology helps in accurately detecting wake words or phrases in speech signals, leading to more reliable and efficient voice-controlled interactions with electronic devices.
Benefits
The benefits of this technology include enhanced user experience, improved accuracy in voice commands, and more seamless interactions with voice-controlled devices.
Potential Commercial Applications
Potential commercial applications of this technology include smart home devices, automotive voice control systems, and customer service chatbots.
Possible Prior Art
One possible prior art for this technology could be existing speech recognition systems used in virtual assistants and smart devices, which may not employ the same advanced machine learning models for wake word detection and response.
Unanswered Questions
How does this technology handle different accents and speech patterns?
The patent application does not provide details on how the machine learning models account for variations in accents and speech patterns that may affect wake word detection accuracy.
What data privacy measures are in place for processing speech signals?
The patent application does not address the data privacy concerns related to processing speech signals for wake word detection and response.
Original Abstract Submitted
a method includes obtaining a speech signal. the method also includes predicting a first likelihood of a wake word or phrase being spoken in the speech signal using a first machine learning model trained to receive the speech signal as input. the method further includes, responsive to the first likelihood exceeding a first threshold, performing automatic speech recognition on the speech signal to determine a textual representation of the speech signal. the method also includes predicting a second likelihood of the wake word or phrase being spoken in the speech signal using a second machine learning model trained to receive at least one of the textual representation, audio features associated with the speech signal, and context features associated with the electronic device. in addition, the method includes, responsive to the second likelihood exceeding a second threshold, generating instructions to perform an action requested in the speech signal.
