Tyre reviews Leao iGreen All Season. Page 14 771

Tires for their price are above all praise.

The tires are good, they are balanced properly. Just in time for our (KhMAO) mid-season.

Satisfied both in winter and summer despite challenging mountain roads in winter

Good tires, in warm weather they don't get soft, while I've been driving at (-3) they don't get stiff, on packed snow and ice there is slippage, in mud they go well, but for winter, winter tires are still needed.

I've already left a review three times. Why does the rating request keep popping up?

I really like the soft rubber, there's almost no noise

Excellent tires, performing well in both warm weather and subzero temperatures with snow and ice.

So far, so good, winter has not come yet

2 years of daily use, without removal... No bubbles, sturdy, not noisy... In short, excellent tires, I recommend

**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 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

2. The system of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing to identify salient patterns.

3. A 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; and providing the extracted text and salient patterns to a notetaking application.

4. The method of claim 3, wherein the activity detection module uses a combination of audio and contextual data to detect starting conditions for data extraction, and the speech recognition module uses deep learning algorithms to identify salient patterns.

5. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and contextual information; 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.

6. The method of claim 5, wherein the speech recognition module uses a machine learning model to process the audio data and identify salient patterns, and the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

7. A 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

8. The system of claim 7, wherein the activity detection module uses a rule-based approach to detect starting conditions for data extraction, and the speech recognition module uses a statistical model to identify salient patterns.

9. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: means for detecting starting conditions for data extraction; means for processing the audio data using speech recognition and pattern detection modules; and means for providing the extracted text and salient patterns to a notetaking application.

10. The system of claim 9, wherein the means for detecting starting conditions for data extraction uses a combination of machine learning and rule-based approaches, and the means for processing the audio data uses deep learning algorithms to identify salient patterns.

11. A method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and contextual information; 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.

12. The method of claim 11, wherein the processing step uses natural language processing to identify salient patterns, and the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

13. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

14. The system of claim 13, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses statistical models to identify salient patterns.

15. 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; and providing the extracted text and salient patterns to a notetaking application.

16. The method of claim 15, wherein the detecting step uses a combination of audio and contextual data to detect starting conditions for data extraction, and the processing step uses deep learning algorithms to identify salient patterns.

17. A system for automatically capturing information from audio data and computer operating context, comprising: means for detecting starting conditions for data extraction; means for processing the audio data using speech recognition and pattern detection modules; and means for providing the extracted text and salient patterns to a notetaking application.

18. The system of claim 17, wherein the means for detecting starting conditions for data extraction uses a rule-based approach, and the means for processing the audio data uses natural language processing to identify salient patterns.

19. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

20. The system of claim 19, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses statistical models to identify salient patterns.

21. A method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and contextual information; 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.

22. The method of claim 21, wherein the processing step uses deep learning algorithms to identify salient patterns, and the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

23. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

24. The system of claim 23, wherein the activity detection module uses a combination of machine learning and rule-based approaches to detect starting conditions for data extraction, and the speech recognition module uses natural language processing to identify salient patterns.

25. 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; and providing the extracted text and salient patterns to a notetaking application.

26. The method of claim 25, wherein the detecting step uses audio and contextual data to detect starting conditions for data extraction, and the processing step uses statistical models to identify salient patterns.

27. A system for automatically capturing information from audio data and computer operating context, comprising: means for detecting starting conditions for data extraction; means for processing the audio data using speech recognition and pattern detection modules; and means for providing the extracted text and salient patterns to a notetaking application.

28. The system of claim 27, wherein the means for detecting starting conditions for data extraction uses a machine learning model, and the means for processing the audio data uses deep learning algorithms to identify salient patterns.

29. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

30. The system of claim 29, wherein the activity detection module uses a combination of audio and contextual data to detect starting conditions for data extraction, and the speech recognition module uses natural language processing to identify salient patterns.

31. A method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and contextual information; 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.

32. The method of claim 31, wherein the processing step uses deep learning algorithms to identify salient patterns, and the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

33. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

34. The system of claim 33, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses statistical models to identify salient patterns.

35. 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; and providing the extracted text and salient patterns to a notetaking application.

36. The method of claim 35, wherein the detecting step uses a combination of audio and contextual data to detect starting conditions for data extraction, and the processing step uses deep learning algorithms to identify salient patterns.

37. A system for automatically capturing information from audio data and computer operating context, comprising: means for detecting starting conditions for data extraction; means for processing the audio data using speech recognition and pattern detection modules; and means for providing the extracted text and salient patterns to a notetaking application.

38. The system of claim 37, wherein the means for detecting starting conditions for data extraction uses a rule-based approach, and the means for processing the audio data uses natural language processing to identify salient patterns.

39. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

40. The system of claim 39, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses statistical models to identify salient patterns.

Claim 1. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

Claim 2. The system of claim 1, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses statistical models to identify salient patterns.

Claim 3. A method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and contextual information; 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.

Claim 4. The method of claim 3, wherein the processing step uses deep learning algorithms to identify salient patterns, and the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

Claim 5. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

Claim 6. The system of claim 5, wherein the activity detection module uses a combination of audio and contextual data to detect starting conditions for data extraction, and the speech recognition module uses natural language processing to identify salient patterns.

Claim 7. A system for automatically capturing information from audio data and computer operating context, comprising: means for detecting starting conditions for data extraction; means for processing the audio data using speech recognition and pattern detection modules; and means for providing the extracted text and salient patterns to a notetaking application.

Claim 8. The system of claim 7, wherein the means for detecting starting conditions for data extraction uses a rule-based approach, and the means for processing the audio data uses deep learning algorithms to identify salient patterns.

Claim 9. 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; and providing the extracted text and salient patterns to a notetaking application.

Claim 10. The method of claim 9, wherein the detecting step uses a combination of audio and contextual data to detect starting conditions for data extraction, and the processing step uses statistical models to identify salient patterns.

Claim 11. A 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

Claim 12. The system of claim 11, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses natural language processing to identify salient patterns.

Claim 13. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

Claim 14. The system of claim 13, wherein the activity detection module uses a combination of audio and contextual data to detect starting conditions for data extraction, and the speech recognition module uses deep learning algorithms to identify salient patterns.

Claim 15. A method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and contextual information; 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.

Claim 16. The method of claim 15, wherein the processing step uses statistical models to identify salient patterns, and the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

Claim 17. A system for automatically capturing information from audio data and computer operating context, comprising: means for detecting starting conditions for data extraction; means for processing the audio data using speech recognition and pattern detection modules; and means for providing the extracted text and salient patterns to a notetaking application.

Claim 18. The system of claim 17, wherein the means for detecting starting conditions for data extraction uses a rule-based approach, and the means for processing the audio data uses natural language processing to identify salient patterns.

Claim 19. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

Claim 20. The system of claim 19, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses statistical models to identify salient patterns.

Claim 21. A 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; and providing the extracted text and salient patterns to a notetaking application.

Claim 22. The method of claim 21, wherein the detecting step uses a combination of audio and contextual data to detect starting conditions for data extraction, and the processing step uses deep learning algorithms to identify salient patterns.

Claim 23. A 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

Claim 24. The system of claim 23, wherein the activity detection module uses a combination of audio and contextual data to detect starting conditions for data extraction, and the speech recognition module uses natural language processing to identify salient patterns.

Claim 25. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and contextual information; 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.

Claim 26. The method of claim 25, wherein the processing step uses statistical models to identify salient patterns, and the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

Claim 27. A system for automatically capturing information from audio data and computer operating context, comprising: means for detecting starting conditions for data extraction; means for processing the audio data using speech recognition and pattern detection modules; and means for providing the extracted text and salient patterns to a notetaking application.

Claim 28. The system of claim 27, wherein the means for detecting starting conditions for data extraction uses a rule-based approach, and the means for processing the audio data uses deep learning algorithms to identify salient patterns.

Claim 29. 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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to an electronic document.

Claim 30. The system of claim 29, wherein the activity detection module uses a machine learning model to detect starting conditions for data extraction, and the speech recognition module uses natural language processing to identify salient patterns.