轮胎评价 Doublestar DW09. Страница 3 73

好的轮胎。已经开始雪季了，已经磨合好了。不吵。

這個價格很划算

**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 note-taking 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 note-taking application to provide the extracted text and salient patterns to a user, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context, and the speech recognition module processes the audio data to identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user.

2. The computer system of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to identify salient patterns in the extracted text.

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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context.

4. The method of claim 3, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time.

5. 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 note-taking application to provide the extracted text and salient patterns to the user, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context, and the speech recognition module processes the audio data to identify salient patterns.

6. The computer system of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to identify salient patterns in the extracted text, and the note-taking application provides the extracted text and salient patterns to the user.

7. 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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context.

8. The method of claim 7, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time, and the activity detection module detects starting conditions for data extraction using machine learning algorithms.

9. 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 note-taking application to provide the extracted text and salient patterns to the user, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context, and the speech recognition module processes the audio data to identify salient patterns.

10. The computer system of claim 9, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction, and the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time.

11. 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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context.

12. The method of claim 11, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user, and the activity detection module detects starting conditions for data extraction using machine learning algorithms.

13. 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 note-taking application to provide the extracted text and salient patterns to the user, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context, and the speech recognition module processes the audio data to identify salient patterns.

14. The computer system of claim 13, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction, and the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time.

15. 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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context, and the speech recognition module processes the audio data to identify salient patterns.

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

3. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

4. The system of claim 3, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time.

5. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

6. The method of claim 5, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction, and the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns.

7. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

8. The system of claim 7, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user.

9. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

10. The method of claim 9, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

11. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

12. The system of claim 11, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time.

13. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context.

14. The method of claim 13, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction, and the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns.

15. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

3. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

4. The system of claim 3, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time.

5. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

6. The method of claim 5, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction, and the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns.

7. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

8. The system of claim 7, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user.

9. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

10. The method of claim 9, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

11. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

12. The system of claim 11, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns, and the note-taking application provides the extracted text and salient patterns to the user in real-time.

13. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

14. The method of claim 13, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction, and the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns.

15. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

**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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction.

3. 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 note-taking application to provide the extracted text and salient patterns to the user.

4. The system of claim 3, wherein the speech recognition module uses deep learning techniques to process the audio data and 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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

6. The method of claim 5, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction.

7. 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 note-taking application to provide the extracted text and salient patterns to the user.

8. The system of claim 7, wherein the note-taking application provides the extracted text and salient patterns to the user in real-time.

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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

10. The method of claim 9, wherein the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns.

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 identify salient patterns; and a note-taking application to provide the extracted text and salient patterns to the user.

12. The system of claim 11, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction.

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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

14. The method of claim 13, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns.

15. 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 note-taking application to provide the extracted text and salient patterns to the user.

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context.

2. A computer system for automatically capturing information from audio data and computer operating context.

3. A method for automatically capturing information from audio data and computer operating context.

4. A computer system for automatically capturing information from audio data and computer operating context.

5. A method for automatically capturing information from audio data and computer operating context.

6. A computer system for automatically capturing information from audio data and computer operating context.

7. A method for automatically capturing information from audio data and computer operating context.

8. A computer system for automatically capturing information from audio data and computer operating context.

9. A method for automatically capturing information from audio data and computer operating context.

10. A computer system for automatically capturing information from audio data and computer operating context.

11. A method for automatically capturing information from audio data and computer operating context.

12. A computer system for automatically capturing information from audio data and computer operating context.

13. A method for automatically capturing information from audio data and computer operating context.

14. A computer system for automatically capturing information from audio data and computer operating context.

15. A method for automatically capturing information from audio data and computer operating context.

**Claims**:
1. A computer-implemented method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction.

3. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

4. The system of claim 3, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns.

5. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

6. The method of claim 5, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction.

7. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

8. The system of claim 7, wherein the note-taking application provides the extracted text and salient patterns to the user in real-time.

9. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

10. The method of claim 9, wherein the speech recognition module uses machine learning algorithms to process the audio data and identify salient patterns.

11. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

12. The system of claim 11, wherein the activity detection module uses natural language processing techniques to detect starting conditions for data extraction.

13. A method for automatically capturing information from audio data and computer operating context, the method comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a note-taking application.

14. The method of claim 13, wherein the speech recognition module uses deep learning techniques to process the audio data and identify salient patterns.

15. A computer system for automatically capturing information from audio data and computer operating context, the system 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 note-taking application to provide the extracted text and salient patterns to the user.

**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 audio data to identify salient patterns; and providing extracted text and salient patterns to a note-taking application.

2. The method of claim 1, wherein the detecting step uses machine learning algorithms.

3. 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 note-taking application.

4. The system of claim 3, wherein the speech recognition module uses deep learning techniques.

5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data to identify salient patterns; and providing extracted text and salient patterns to a note-taking application.

6. The method of claim 5, wherein the detecting step uses natural language processing techniques.

7. 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 note-taking application.

8. The system of claim 7, wherein the note-taking application provides extracted text and salient patterns in real-time.

9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data to identify salient patterns; and providing extracted text and salient patterns to a note-taking application.

10. The method of claim 9, wherein the processing step uses machine learning algorithms.

11. 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 note-taking application.

12. The system of claim 11, wherein the activity detection module uses natural language processing techniques.

13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data to identify salient patterns; and providing extracted text and salient patterns to a note-taking application.

14. The method of claim 13, wherein the processing step uses deep learning techniques.

15. 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 note-taking application.

外观不錯，冬天再試試，看看在雪天和結冰的情況下是否會失望。交貨時間很準時。

輪胎超級好，推薦！

其摩擦性能相当不错。
能在雪地和冰面上行驶，刹车性能也很好，ABS系统在相当晚的时刻才会介入。
但是所有这些优点都被一个缺点所掩盖——轮胎不圆，
无论如何平衡，还是轮胎相对于轮圈位置的变化，都无济于事。
只会改变轮胎的振动频率，要么是90，要么是100，要么是110。

輪胎超级好，老公很滿意，我们又訂了3個👍

輪胎彎曲！！！

所有的轮胎都是弯曲的。在正常的轮胎服务中心进行的平衡调节在这里没有帮助。他们改变了轮胎相对于轮毂的位置，也试过翻转轮胎，但是超过90公里每小时的速度时，方向盘仍然会剧烈振动。在轮胎检查机上，当轮子旋转时，轮胎的弯曲明显可见。我将会退货，即使需要通过法律途径

性价比很高的轮胎。