Tyre reviews Nexen N'Priz RH7. Page 2 42

The tires are a bit noisy. They handle dry and wet roads perfectly.

**Reasoning**: The patent draft describes a computer system that automatically captures information from audio data and computer operating context, such as conversations and meetings. The system uses an activity detection module to detect starting conditions for data extraction, and then processes the audio data using speech recognition and pattern detection modules to identify salient patterns. The system provides the extracted text and salient patterns to a notetaking application, which allows users to interactively edit an electronic document incorporating the extracted information. To generate patent claims, we need to identify the key technical features of the invention and ensure that the claims are clear, concise, and consistent with the patent draft.

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using speech recognition and pattern detection modules to identify salient patterns; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the notetaking application provides a user interface to edit the extracted information.

3. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user interface, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

4. The system of claim 3, wherein the activity detection module, speech recognition module, pattern detection module, and notetaking application are integrated to provide a seamless user experience for capturing and editing extracted information.

5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information, wherein the notetaking application provides a user interface to edit the extracted information.

6. The method of claim 5, wherein the speech recognition module uses deep learning algorithms to process the audio data, and the pattern detection module uses natural language processing to identify salient patterns.

7. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides a user interface to edit the extracted information.

8. The system of claim 7, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms, and the notetaking application provides a graphical user interface to edit the extracted information.

9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information, wherein the notetaking application provides a user interface to edit the extracted information.

10. The method of claim 9, wherein the speech recognition module uses convolutional neural networks to process the audio data, and the pattern detection module uses recurrent neural networks to identify salient patterns.

11. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user interface, wherein the system allows users to interactively edit an electronic document incorporating the extracted information.

12. The system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on sensor data, and the notetaking application provides a voice-controlled interface to edit the extracted information.

13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information, wherein the notetaking application provides a cloud-based storage for the extracted information.

14. The method of claim 13, wherein the speech recognition module uses transfer learning to process the audio data, and the pattern detection module uses attention mechanisms to identify salient patterns.

15. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides a real-time feedback to users during the editing process.

However the format should be followed as requested, I will reformat the response to only include claims as follows:

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using speech recognition and pattern detection modules to identify salient patterns; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction.
3. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user interface.
4. The system of claim 3, wherein the activity detection module detects starting conditions for data extraction based on sensor data.
5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information.
6. The method of claim 5, wherein the speech recognition module uses deep learning algorithms to process the audio data.
7. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides a user interface to edit the extracted information.
8. The system of claim 7, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms.
9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information.
10. The method of claim 9, wherein the speech recognition module uses convolutional neural networks to process the audio data.
11. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user interface.
12. The system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on sensor data, and the notetaking application provides a voice-controlled interface to edit the extracted information.
13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information.
14. The method of claim 13, wherein the speech recognition module uses transfer learning to process the audio data.
15. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides a real-time feedback to users during the editing process.

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using speech recognition and pattern detection modules to identify salient patterns; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the notetaking application provides a user interface to edit the extracted information.
3. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user interface, wherein the system allows users to interactively edit an electronic document incorporating the extracted information.
4. The system of claim 3, wherein the activity detection module detects starting conditions for data extraction based on sensor data, and the notetaking application provides a voice-controlled interface to edit the extracted information.
5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information, wherein the notetaking application provides a cloud-based storage for the extracted information.
6. The method of claim 5, wherein the speech recognition module uses deep learning algorithms to process the audio data, and the pattern detection module uses natural language processing to identify salient patterns.
7. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides a real-time feedback to users during the editing process.
8. The system of claim 7, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms, and the notetaking application provides a graphical user interface to edit the extracted information.
9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information, wherein the notetaking application provides a user interface to edit the extracted information.
10. The method of claim 9, wherein the speech recognition module uses convolutional neural networks to process the audio data, and the pattern detection module uses recurrent neural networks to identify salient patterns.
11. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user interface, wherein the system allows users to interactively edit an electronic document incorporating the extracted information.
12. The system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on sensor data, and the notetaking application provides a voice-controlled interface to edit the extracted information.
13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data using speech recognition and pattern detection modules; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document incorporating the extracted information, wherein the notetaking application provides a cloud-based storage for the extracted information.
14. The method of claim 13, wherein the speech recognition module uses transfer learning to process the audio data, and the pattern detection module uses attention mechanisms to identify salient patterns.
15. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides a real-time feedback to users during the editing process.

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context.
2. The method of claim 1, wherein the activity detection module uses machine learning algorithms.
3. A computer system for automatically capturing information from audio data and computer operating context.
4. The system of claim 3, wherein the activity detection module detects starting conditions for data extraction based on sensor data.
5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document.
6. The method of claim 5, wherein the speech recognition module uses deep learning algorithms.
7. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application.
8. The system of claim 7, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms.
9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document.
10. The method of claim 9, wherein the speech recognition module uses convolutional neural networks.
11. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application.
12. The system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on sensor data.
13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing the audio data; providing the extracted text and salient patterns to a notetaking application; and allowing users to interactively edit an electronic document.
14. The method of claim 13, wherein the speech recognition module uses transfer learning.
15. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides a real-time feedback to users during the editing process.

Good tires, perfectly holding the course on the road, both in dry and wet weather. Not very noisy.

In the first season, they showed themselves to be excellent in all parameters, soft, not noisy, however, as it seemed to me, they were prone to slipping in turns. In the second season, small cracks appeared on all 4 tires, I don't know why, I used them both in the city and outside of it sometimes. Noticeable and even stressful aquaplaning started to occur while driving. In general, on a wet road, it behaves carelessly, it's scary. But in other respects, you can drive on them. I don't know how they behave on sedans, maybe it's different.

For a crossover, that's what you need

Normal tires, a bit stiff.

Very noisy tires. Apparently made in Korea, but it's impossible to drive, it's like flying on an airplane. Will be selling

The tires are good, I liked them

Good.

The tire was to my liking.