Tyre reviews Sailun Atrezzo ZSR 2. Page 7 1524
- The product was purchased at Mosautoshina
- Rate
Normal tire. Holds the road well. Didn't drive much in the rain. Balanced well. In general, I have no particular complaints about the tire. I bought the tires for 6 thousand per unit. I wanted to take Bridgestones. I think if I had taken Bridgestones for 12 thousand per unit, I wouldn't have seen any difference. So, I join the majority of opinions that there is no point in overpaying for a brand.
- Vehicle:
- Subaru Forester
- Size:
- 215/55 R17 98W XL
- Buy again?:
- Most likely
- City:
- Сочи
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability
- The product was purchased at Mosautoshina
- Rate
Switched to this tire from Michelin Pilot Sport 4 in the same exact size, but in fact, Sailun is a bit "wider". The tire withstood very strong potholes, but gave up when strongly hit by a cut asphalt :( In the best case scenario, only a run flat would have withstood such an impact)
On "dry" roads, the grip is excellent, but when driving "on the limit" (sharp braking, passing turns at high speed), compared to Michelin, I can note a slightly worse grip, which manifested in a slight squeal of the tire. Overall, it's a bit noisier than Michelin.
On "wet" roads, or rather when driving through puddles at high speed, I can note a tendency to aquaplaning. But I think it's a matter of speed, not the tire.
The price decides everything - the price/quality ratio is at the highest level. I also have Sailun winter tires - I had to repair them once, and the tire fitter noted the excellent composition of the rubber.
- Vehicle:
- Skoda Octavia
- Size:
- 225/40 R18 92Y XL
- Buy again?:
- Definitely yes
- City:
- Самара
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability
- Rate
Tire size R20 245/35
Pros:
1. Thick sidewall cord
2. Wheel protection from rubbing against the curb
3. Resistance to bulging
4. Not bad grip on dry road (better on wet)
5. Wear resistance
6. Adequate price
7. Managed to drive on these tires in the snow and they performed confidently (however, it's worth noting that the trip was immediately after tire replacement, i.e. the tires were new and without mileage)
Cons:
1. Quite loud and hard rubber (resulting in noise), however, this parameter is completely irrelevant to me, since such rubber is more resistant to potholes
Comment on the tires: want more massive protection from rubbing against the curbs- Vehicle:
- Mazda 6
- Buy again?:
- Definitely yes
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability
- The product was purchased at Mosautoshina
- Rate
**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 a user interface, wherein the user interface allows users to interactively edit an electronic document incorporating the extracted information.
2. The system 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 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 detects starting conditions for data extraction based on the audio data and computer operating context, and the notetaking application provides an interactive user interface to edit the extracted information.
5. A computer-readable medium having stored thereon a set of instructions for automatically capturing information from audio data and computer operating context, comprising: instructions for detecting starting conditions for data extraction; instructions for processing the audio data using speech recognition and pattern detection modules; and instructions for providing the extracted text and salient patterns to a notetaking application.
6. The computer-readable medium of claim 5, wherein the instructions for detecting starting conditions for data extraction use machine learning algorithms based on the audio data and computer operating context.
7. A system for automatically capturing information from audio data and computer operating context, comprising: a means for detecting starting conditions for data extraction; a means for processing the audio data using speech recognition and pattern detection modules; and a means for providing the extracted text and salient patterns to a notetaking application.
8. The system of claim 7, wherein the means for detecting starting conditions for data extraction uses an activity detection module to detect starting conditions 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 detecting starting conditions for data extraction uses machine learning algorithms based on the audio data and computer operating context.
11. 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 a notetaking application to provide the extracted text and salient patterns to a user interface.
12. The computer system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on the audio data and computer operating context.
13. A computer-readable medium having stored thereon a set of instructions for automatically capturing information from audio data and computer operating context, comprising: instructions for detecting starting conditions for data extraction; instructions for processing the audio data using speech recognition and pattern detection modules; and instructions for providing the extracted text and salient patterns to a notetaking application.
14. The computer-readable medium of claim 13, wherein the instructions for detecting starting conditions for data extraction use machine learning algorithms based on the audio data and computer operating context.
15. 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.**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 a notetaking application to provide the extracted text and salient patterns to a user interface.
2. The computer system of claim 1, wherein the activity detection module detects starting conditions for data extraction based on the audio data and computer operating context.
3. 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.
4. The method of claim 3, wherein the detecting starting conditions for data extraction uses machine learning algorithms based on the audio data and computer operating context.
5. A computer-readable medium having stored thereon a set of instructions for automatically capturing information from audio data and computer operating context, comprising: instructions for detecting starting conditions for data extraction; instructions for processing the audio data using speech recognition and pattern detection modules; and instructions for providing the extracted text and salient patterns to a notetaking application.
6. The computer-readable medium of claim 5, wherein the instructions for detecting starting conditions for data extraction use machine learning algorithms based on the audio data and computer operating context.
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.
8. The system of claim 7, wherein the means for detecting starting conditions for data extraction uses an activity detection module to detect starting conditions 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 detecting starting conditions for data extraction uses machine learning algorithms based on the audio data and computer operating context.
11. 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 a notetaking application to provide the extracted text and salient patterns to a user interface.
12. The computer system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on the audio data and computer operating context.
13. A computer-readable medium having stored thereon a set of instructions for automatically capturing information from audio data and computer operating context, comprising: instructions for detecting starting conditions for data extraction; instructions for processing the audio data using speech recognition and pattern detection modules; and instructions for providing the extracted text and salient patterns to a notetaking application.
14. The computer-readable medium of claim 13, wherein the instructions for detecting starting conditions for data extraction use machine learning algorithms based on the audio data and computer operating context.
15. 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.- Size:
- 225/45 R18 95Y XL
- Rate
- The product was purchased at Mosautoshina
- Rate
Everything is fine
- Vehicle:
- Skoda Octavia
- Size:
- 215/50 R17 95W XL
- Buy again?:
- Most likely
- City:
- Saint Petersburg
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability
- The product was purchased at Mosautoshina
- Rate
Excellent tires, pleasantly surprised. They handle both dry and wet roads perfectly, behave adequately in both ruts and puddles, and cope well with X-Drive. After 160 they are very noisy, no other complaints.
- Vehicle:
- BMW 5 Series
- Size:
- 245/45 R18 100Y XL
- Buy again?:
- Definitely yes
- City:
- Moscow
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability
- The product was purchased at Mosautoshina
- Rate
Driven 5,000 km, overall impression is positive. But there is a nuance - on one wheel - 70g of balancing weights...
- Vehicle:
- ВАЗ Vesta
- Size:
- 205/50 R17 93W XL
- Buy again?:
- Most likely
- City:
- Saint Petersburg
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability
- The product was purchased at Mosautoshina
- Rate
Excellent non-noisy tires. Good grip on water. Not noisy. Price-quality ratio is corresponding
- Vehicle:
- Subaru Legacy
- Buy again?:
- Definitely yes
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability
- The product was purchased at Mosautoshina
- Rate
Excellent tires for the money, they hold great in the rain, are quiet and don't make noise, and bumps are passed smoothly. I haven't caught any large potholes, hopefully, I won't catch any. They don't float or beat. The balancing turned out to be 15 on each wheel. Two wheels had to be turned 180 degrees. In general, I'm completely satisfied. Let's see how long they will last
- Vehicle:
- Toyota Corolla
- Size:
- 215/50 R17 95W
- Buy again?:
- Most likely
- City:
- Губкин
- Control on a dry road
- Steering in the wet
- Course stability
- Drive comfort
- Quiet in motion
- Braking efficiency
- Resistant to aquaplaning
- Velocity characteristics
- Wearability
- Quality of production
- Price justifiability

