Tyre reviews Sailun Atrezzo ZSR. Page 28 1058

The first thing that pleased me was the thick tread, the second was the price
the third was the soft and quiet ride in comparison to Kumho summer tires, soft probably due to the nitrogen, not a big deal.
The downside is that when braking at 80 km/h, they already start to skid, another downside is that after 120 km/h, there is a vibration, as others have written.
If you drive in the city, this is the ideal tire, 100 out of 100
I wouldn't recommend it for the highway.

Before buying, I had BRIDGESTONE, I didn't notice any differences, everything suited me. Perfect replacement

Bought two tires, one turned out to be uneven with a 40-60 gram imbalance. After reading reviews, I realized they won't replace it. Didn't bother to contact anyone. I'm driving slowly.

Very good

I like them, they're not noisy, aquaplaning is fine.

Excellent tires.

Excellent tires, balanced well. Made in the 52nd week of 23 (5223)???????

Great tire, still need to find out about wear resistance

Hello! I'm buying tires from this manufacturer for the first time. Time will tell how they perform. The seller shipped promptly, WB delivery is excellent. Thank you!

**Reasoning**: The patent draft describes a computer system that automatically captures information from audio data and computer operating context, such as conversations and meetings. To generate patent claims, we need to identify the key technical features of the invention, including the activity detection module, speech recognition, and pattern detection. The claims should cover the key aspects of the invention, including the system's functionality and technical features.

**Claims**:
1. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module, a speech recognition module, and a pattern detection module.
2. The system of claim 1, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context.
3. The system of claim 1, further comprising a speech recognition module that processes audio data to identify relevant information.
4. The system of claim 1, wherein the pattern detection module identifies salient information from the extracted text.
5. A method for automatically capturing information from audio data and computer operating context, comprising the steps of: detecting starting conditions for data extraction, processing audio data using speech recognition, and identifying salient information using pattern detection.
6. The method of claim 5, further comprising the step of providing the extracted information to a notetaking application.
7. A computer-readable medium having stored thereon a set of instructions for causing a computer to automatically capture information from audio data and computer operating context.
8. The computer-readable medium of claim 7, wherein the instructions cause the computer to detect starting conditions for data extraction based on audio data and computer operating context.
9. 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 audio data using speech recognition, and means for identifying salient information using pattern detection.
10. The system of claim 9, wherein the means for detecting starting conditions for data extraction are based on machine learning algorithms.
11. A method for automatically capturing information from audio data and computer operating context, comprising the steps of: detecting starting conditions for data extraction, processing audio data using speech recognition, identifying salient information using pattern detection, and providing the extracted information to a notetaking application.
12. The method of claim 11, further comprising the step of storing the extracted information in a database for later retrieval.
13. A computer 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.
14. The system of claim 13, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context.
15. A computer-readable medium having stored thereon a set of instructions for causing a computer to automatically capture information from audio data and computer operating context, and to provide the extracted information to a notetaking application.

**Claims**:
1. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module, a speech recognition module, and a pattern detection module.
2. The system of claim 1, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context.
3. The system of claim 1, further comprising a notetaking application that receives the extracted information from the pattern detection module.
4. A method for automatically capturing information from audio data and computer operating context, comprising the steps of: detecting starting conditions for data extraction, processing audio data using speech recognition, and identifying salient information using pattern detection.
5. The method of claim 4, wherein the step of detecting starting conditions for data extraction is based on machine learning algorithms.
6. A computer-readable medium having stored thereon a set of instructions for causing a computer to automatically capture information from audio data and computer operating context.
7. The computer-readable medium of claim 6, wherein the instructions cause the computer to detect starting conditions for data extraction based on audio data and computer operating context.
8. 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 audio data using speech recognition, and means for identifying salient information using pattern detection.
9. The system of claim 8, wherein the means for detecting starting conditions for data extraction are based on machine learning algorithms.
10. A method for automatically capturing information from audio data and computer operating context, comprising the steps of: detecting starting conditions for data extraction, processing audio data using speech recognition, identifying salient information using pattern detection, and providing the extracted information to a notetaking application.