轮胎评价 Viatti Strada Asimmetrico. 页面 121 3250
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总体来说还不错,但是……
但是噪音非常大,有时甚至收音机都无法掩盖。
下次我会更倾向于选择科迪昂轮胎。- 车辆:
- Lada Vesta SW Cross
- 尺寸:
- 205/55 R16 91V
- 是否会再次购买?:
- 不太可能
- 城市:
- 卡卢加
- 干燥道路操控
- 湿润道路操控
- 直线行驶稳定性
- 行驶舒适度
- 行驶中的低噪音水平
- 制动效能
- 抗水漂能力
- 速度特性
- 耐磨性
- 制造质量
- 性价比
- 商品在莫萨夫托什娜购买
- 评分
**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 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 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 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 detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
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; 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.
6. The method of claim 5, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
7. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
8. The system of claim 7, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
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; 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.
10. The method of claim 9, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
11. 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 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 detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
13. 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.
14. The method of claim 13, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
15. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
16. The system of claim 15, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
17. 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; 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.
18. The method of claim 17, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
19. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
20. The system of claim 19, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 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.
Claim 2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 4. The system of claim 3, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 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; 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.
Claim 6. The method of claim 5, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 7. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 8. The system of claim 7, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 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; 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.
Claim 10. The method of claim 9, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 11. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 12. The system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 13. 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.
Claim 14. The method of claim 13, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 15. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 16. The system of claim 15, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 17. 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; 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.
Claim 18. The method of claim 17, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 19. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 20. The system of claim 19, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 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.
Claim 2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 4. The system of claim 3, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 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; 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.
Claim 6. The method of claim 5, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 7. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 8. The system of claim 7, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 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; 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.
Claim 10. The method of claim 9, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 11. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 12. The system of claim 11, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 13. 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.
Claim 14. The method of claim 13, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 15. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 16. The system of claim 15, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
Claim 17. 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; 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.
Claim 18. The method of claim 17, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on audio data and computer operating context.
Claim 19. 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 audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
Claim 20. The system of claim 19, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, including audio signals and user interactions.
- 车辆:
- Toyota Corolla
- 是否会再次购买?:
- 很可能
- 干燥道路操控
- 湿润道路操控
- 直线行驶稳定性
- 行驶舒适度
- 行驶中的低噪音水平
- 制动效能
- 抗水漂能力
- 速度特性
- 耐磨性
- 制造质量
- 性价比
- 商品在莫萨夫托什娜购买
- 评分
好的)
- 尺寸:
- 195/65 R15 91H
- 评分
- 商品在莫萨夫托什娜购买
- 评分
價格和品質可以接受,夏天使用略顯重和噪音大,其餘方面是非常好的輪胎。
- 车辆:
- Hyundai Elantra
- 尺寸:
- 195/65 R15 91H
- 是否会再次购买?:
- 肯定会
- 城市:
- 波多利斯克
- 干燥道路操控
- 湿润道路操控
- 行驶舒适度
- 直线行驶稳定性
- 行驶中的低噪音水平
- 制动效能
- 抗水漂能力
- 速度特性
- 耐磨性
- 制造质量
- 性价比
- 商品在莫萨夫托什娜购买
- 评分
一切都符合要求
- 尺寸:
- 185/65 R14 86H
- 评分
- 商品在莫萨夫托什娜购买
- 评分
价格合理的轮胎是在同价位的范围内。
- 车辆:
- Skoda Rapid
- 尺寸:
- 185/60 R15 84H
- 是否会再次购买?:
- 很可能
- 城市:
- 圣彼得堡
- 干燥道路操控
- 湿润道路操控
- 直线行驶稳定性
- 行驶舒适度
- 行驶中的低噪音水平
- 制动效能
- 抗水漂能力
- 速度特性
- 耐磨性
- 制造质量
- 性价比
- 商品在莫萨夫托什娜购买
- 评分
優秀的輪胎,已經裝上了👍😉
- 尺寸:
- 175/70 R13 82H
- 评分
- 商品在莫萨夫托什娜购买
- 评分
好像一切都还可以
- 车辆:
- Toyota Corolla
- 尺寸:
- 175/70 R14 84H
- 是否会再次购买?:
- 肯定会
- 城市:
- 莫斯科
- 干燥道路操控
- 湿润道路操控
- 行驶舒适度
- 直线行驶稳定性
- 行驶中的低噪音水平
- 制动效能
- 抗水漂能力
- 速度特性
- 耐磨性
- 制造质量
- 性价比
- 商品在莫萨夫托什娜购买
- 评分
好的輪胎!????
- 尺寸:
- 185/65 R15 88H
- 评分


