18072876. DYNAMIC SPEECH ENHANCEMENT COMPONENT OPTIMIZATION simplified abstract (Microsoft Technology Licensing, LLC)
Contents
DYNAMIC SPEECH ENHANCEMENT COMPONENT OPTIMIZATION
Organization Name
Microsoft Technology Licensing, LLC
Inventor(s)
Ross G. Cutler of Clyde Hill WA (US)
William D. Fallas Cordero of Belen (CR)
DYNAMIC SPEECH ENHANCEMENT COMPONENT OPTIMIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18072876 titled 'DYNAMIC SPEECH ENHANCEMENT COMPONENT OPTIMIZATION
Simplified Explanation
The patent application describes a method for optimizing speech enhancement components in speech communication systems using non-intrusive speech quality assessment. Here are the key points:
- The method involves receiving audio data, including speech, from a computing device over a network.
- A trained non-intrusive speech quality assessment (NISQA) model is used to detect the quality of the speech in the audio data automatically.
- The method determines whether the computing device is a low-quality endpoint based on the detected speech quality.
- If the computing device is determined to be a low-quality endpoint, at least one speech enhancement component is transferred from the computing device to at least one server device over the network.
Potential applications of this technology:
- Speech communication systems: This technology can be applied to optimize speech enhancement components in various speech communication systems, such as VoIP (Voice over Internet Protocol) systems, video conferencing systems, and telephony systems.
- Call centers: The technology can be used to improve the speech quality in call centers, ensuring better communication between agents and customers.
- Remote meetings: This innovation can enhance the speech quality in remote meetings, improving the overall audio experience for participants.
Problems solved by this technology:
- Low-quality endpoints: The method helps identify low-quality endpoints in speech communication systems, allowing for targeted optimization to improve the speech quality.
- Non-intrusive assessment: The use of a trained NISQA model enables automatic detection of speech quality without requiring intrusive methods, such as subjective user feedback or manual evaluation.
Benefits of this technology:
- Enhanced speech quality: By optimizing speech enhancement components based on the detected speech quality, this technology can significantly improve the clarity and intelligibility of speech in communication systems.
- Efficient resource allocation: The method allows for targeted allocation of speech enhancement components to low-quality endpoints, optimizing the use of resources and improving overall system performance.
- Seamless integration: The ability to transfer speech enhancement components from computing devices to server devices over the network ensures a seamless integration of the optimization process into existing speech communication systems.
Original Abstract Submitted
Systems, methods, and computer-readable storage devices are disclosed for optimizing speech enhancement components to use in speech communication systems using non-intrusive speech quality assessment. One method including: receiving, from a computing device over a network, audio data, the audio data including speech; detecting a first quality of the speech of the audio data using a trained non-intrusive speech quality assessment (NISQA) model, the trained NISQA model trained to detect quality of speech automatically; determining whether the computing device is a low-quality endpoint based on the first quality of speech of the audio data; and transferring, from the computing device over the network, at least one speech enhancement component to at least one server device when the computing device is determined to be a low-quality endpoint.
