Tyre reviews Continental ContiSportContact 6 93

Used on a rally car, driven on a test track in various conditions. The tire is fantastic, on wet road, dry road, sand and even driven over a barrier to test side-slip.

Didn't make a mistake :). Worthy tires

Sportcontact 5 on a wet road were not great and aquaplaning was a problem too, but I don't feel those downsides with the Sportcontact 6 anymore :). I highly recommend this tire, it's worth its price! Soft and stable, on both wet and dry roads.

The magnificent tire has replaced the SportContact 5P.
An excellent resistance to damage at 35 profile, ideal braking on both dry and wet asphalt. Excellent handling. No vibrations at all, very comfortable for low-profile tires.
Quiet, protective sidewall very effectively protects the disc. Excellent manufacturing quality.
For BMW with increased wear of the side parts of the tread, we would have liked a greater depth in these areas, as the tread in the middle is still deep

I'm buying the seventh set, not just for my car! I'm satisfied with the tires. My manager, Igor Aptikeev, handles orders promptly, answers phone calls even on weekends, and keeps me updated on order status outside of working hours – everything is done correctly! Unfortunately, I can't say the same about the Rostov branch at Korolev Prospekt 5/2! On the last working day before the May holidays, the department couldn't collect the order from the

This is not rubber, it's a masterpiece. Out of all the Pirelli, Yokohama, and GoodYear I've had in my life, this is the best. The 245×35 R20 turned out to be SOFTER than my 6-year-old 17-inch wheels. The Black Chili compound is a bomb, incredibly quiet. The quietest tire I've ever had. I thought for sure it would be noisy with the Zico profile, but everything turned out to be much more pleasant. The car is a Lexus ES 7th generation.

Disappointed with the first Conti tire, size 28535 ZR R22 100Y on my Audi Q7. Acoustic comfort is only 2 out of 5! Throughout the entire journey, a quite audible ringing hum is constantly present, which becomes more pronounced with increasing speed. It's tolerable up to 70 km/h, but beyond that it gets louder, in my opinion, even louder than a winter studded Conti (R20). Pressure is at 2

Great tires, quiet and no humming. One minus, they are nails. Nails love these tires) till the end were Pirelli, no problems with nails. Maybe coincidence. Currently, I want to sell my set and buy a new one. I'll probably buy them again, as there is no other choice of tires in size 295/30/22, 335/25/22.

Received two tires Portugal 2023-2024. Two tires Czech Republic 2025. The tires are different not only in the year of manufacture but also in appearance. Portugal is noticeably stiffer. Paying over a hundred thousand for tires with a speed index of 300km/h and getting a assembled "mess" is unacceptable. You need to have a more lively connection with the warehouse. I regret getting involved with your company.

**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; 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 based on the audio data and computer operating context.
3. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing the audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
4. The system of claim 3, wherein the activity detection module uses natural language processing to detect starting conditions for data extraction based on the audio data and computer operating context.
5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using machine learning algorithms; processing the audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application.
6. The method of claim 5, wherein the speech recognition module uses deep learning algorithms to process the audio data and 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.
8. The system of claim 7, wherein the pattern detection module uses rule-based algorithms to identify salient patterns based on the audio data and computer operating context.
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; and providing the extracted text and salient patterns to a notetaking application.
10. The method of claim 9, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information using a graphical user interface.
11. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing the audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
12. The system of claim 11, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the audio data and computer operating context.
13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using natural language processing; processing the audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application.
14. The method of claim 13, wherein the speech recognition module uses deep learning algorithms to process the audio data and identify salient patterns based on the computer operating context.
15. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing the audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.

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

So far, everything is more than satisfactory - both high-speed behavior and handling in general, and in heavy rain, and the noise level.
Good quality tires