Tyre reviews Yokohama Bluearth ES32. Page 85 2151

  • Yokohama Bluearth ES32
    Yokohama Bluearth ES32

Статистика отзывов на шины Yokohama Bluearth ES32

Ниже отображены сводные характеристики шины, основанные на отзывах и оценках автовладельцев со всего мира.
При учёте общей оценки летней шины её показатели на снегу и льду не учитываются.

  • Средняя оценка шин Yokohama Bluearth ES32 пользователями сайта: 4.78058 из 5
  • Количество отзывов на шины Yokohama Bluearth ES32: 2160 шт.
  • Место в рейтинге: 297
  • Место в рейтинге (летние): 181
Control on a dry road
Steering in the wet
Drive comfort
Quiet in motion
Braking efficiency
Resistant to aquaplaning
Velocity characteristics
Wearability
Quality of production
Price justifiability
Все оценки пользователей
Оценки реальных покупателей

Оценки шин Yokohama Bluearth ES32 по месяцам

По распределению
оценок

1
1%
2
1%
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1%
4
6%
5
91%
  • about tyre Yokohama Bluearth ES32

    Rate
    5

    I've driven on tires from almost all top brands (Bridgestone, Continental, Michelin, Pirelli, and more affordable ones: Yokohama, Toyo, Matador), previously I only bought products from Japan, Malaysia, and Europe. These tires made in Russia have surpassed everything I've driven on before. Handling, comfort, quietness, fuel efficiency, and aquaplaning resistance are like a knife through butter, at reasonable speeds, of course. Wear after 30,000 km is almost imperceptible. The engineers and chemists have done an excellent job, Respect!

    Vehicle:
    Volkswagen Polo Sedan
    Buy again?:
    Definitely yes
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    Rate
    4.9

    Good, soft rubber 4 season, I'm driving, it will definitely last for 1 more season

    Vehicle:
    Renault Sandero
    Buy again?:
    Most likely
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    The product was purchased at Mosautoshina
    Rate
    5

    **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 ensure that the claims are clear, concise, and consistent with the patent draft, we need to identify the key technical features of the invention and ensure that the claims cover the essential aspects of the invention.

    **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 based on the computer operating context, including the user's location, time, and other relevant factors.

    3. A computer system for automatically capturing information from audio data and computer operating context, comprising: a processor; a memory; and an activity detection module, wherein the activity detection module detects starting conditions for data extraction based on the audio data and computer operating context.

    4. The system of claim 3, wherein the processor processes the audio data using speech recognition and pattern detection modules to identify salient patterns, and provides the extracted text and salient patterns to a notetaking application.

    5. 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 to identify salient patterns; providing the extracted text and salient patterns to a notetaking application; and interactively editing an electronic document incorporating the extracted information.

    6. The method of claim 5, wherein the activity detection module uses natural language processing algorithms to detect starting conditions for data extraction based on the computer operating context.

    7. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: a processor; a memory; an activity detection module; and a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

    8. The system of claim 7, wherein the processor processes the audio data using machine learning algorithms to identify salient patterns, and provides the extracted text and salient patterns to the notetaking application.

    9. 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 to identify salient patterns; providing the extracted text and salient patterns to a notetaking application; and interactively editing an electronic document incorporating the extracted information.

    10. The method of claim 9, wherein the activity detection module uses deep learning algorithms to detect starting conditions for data extraction based on the computer operating context, including the user's location, time, and other relevant factors.

    11. A computer-implemented system for automatically capturing information from audio data and computer operating context, comprising: a processor; a memory; an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.

    12. The system of claim 11, wherein the processor processes the audio data using natural language processing algorithms to identify salient patterns, and provides the extracted text and salient patterns to the notetaking application.

    13. 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 to identify salient patterns; providing the extracted text and salient patterns to a notetaking application; and interactively editing an electronic document incorporating the extracted information.

    14. The method of claim 13, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.

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

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

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

    Vehicle:
    Renault Logan
    Size:
    185/70 R14 88H
    Buy again?:
    Most likely
    City:
    Владимир
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    The product was purchased at Mosautoshina
    Rate
    4.9

    Size 195/60/15
    They handle the road well on different surfaces, no drift is felt in turns, and the handling is predictable.
    Over the season, it ate 2mm of tread.
    A relative bought the same ones for a Skoda Fabia, also satisfied.

    Vehicle:
    Renault Logan
    Size:
    185/60 R14 82H
    Buy again?:
    Most likely
    City:
    Moscow
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    The product was purchased at Mosautoshina
    Rate
    4.1

    Seem to be good tires. Haven't driven much, but so far so good.

    Vehicle:
    ВАЗ Kalina
    Size:
    185/60 R14 82H
    Buy again?:
    Most likely
    City:
    Череповец
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    The product was purchased at Mosautoshina
    Rate
    5

    It's just a genius product!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

    Vehicle:
    Toyota Corolla
    Size:
    205/55 R16 91V
    Buy again?:
    Definitely yes
    City:
    Yaroslavl
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    The product was purchased at Mosautoshina
    Rate
    4

    Soft rubber. Stable in rut.

    Vehicle:
    Kia Cee'd
    Size:
    205/55 R16 91V
    Buy again?:
    Most likely
    City:
    Noginsk
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    The product was purchased at Mosautoshina
    Rate
    3.9

    Good tires for a calm driving style, quiet.

    Vehicle:
    Toyota Sprinter Carib
    Size:
    175/65 R14 82H
    Buy again?:
    Most likely
    City:
    Оренбург
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    Rate
    4.6

    Good tires, soft and comfortable, while normally driving on dirt roads.

    Vehicle:
    Hyundai Creta
    Buy again?:
    Most likely
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability
  • about tyre Yokohama Bluearth ES32

    Rate
    4.8

    Good tires in terms of "price-quality" ratio.

    Vehicle:
    Volkswagen Polo
    Buy again?:
    Most likely
    Control on a dry road
    Steering in the wet
    Drive comfort
    Course stability
    Quiet in motion
    Braking efficiency
    Resistant to aquaplaning
    Velocity characteristics
    Wearability
    Quality of production
    Price justifiability