Tyre reviews Doublestar DSU02. Страница 6 305

Excellent tires

Looks nice, haven't tried it on the go yet

Handles well, not noisy, balances perfectly

Arrived on time, thank you to the seller

**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.

2. The system of claim 1, where the activity detection module uses machine learning algorithms to identify relevant 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 user.

4. The method of claim 3, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context.

5. A computer-readable medium having computer-executable instructions for performing the method of claim 3, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

6. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

7. A method for training the activity detection module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the activity detection module.

8. The method of claim 7, wherein the machine learning model is trained using deep learning techniques and the activity detection module detects starting conditions for data extraction based on the trained model.

9. A computer system for automatically capturing information from audio data and computer operating context, comprising: a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a note-taking application to provide the extracted text and salient patterns to a user.

10. The system of claim 9, wherein the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

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 speech recognition and pattern detection modules; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

12. The method of claim 11, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms and the speech recognition module uses deep learning techniques to process the audio data.

13. A computer-readable medium having computer-executable instructions for performing the method of claim 11, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

14. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

15. A method for training the speech recognition module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the speech recognition module.

16. The method of claim 15, wherein the machine learning model is trained using natural language processing techniques and the speech recognition module uses the trained model to process the audio data.

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

18. The system of claim 17, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses deep learning techniques to process the audio data.

19. 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; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

20. The method of claim 19, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, and the speech recognition module uses natural language processing techniques to process the audio data.

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

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

Claim 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; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

Claim 4. The method of claim 3, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context.

Claim 5. A computer-readable medium having computer-executable instructions for performing the method of claim 3, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

Claim 6. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

Claim 7. A method for training the activity detection module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the activity detection module.

Claim 8. The method of claim 7, wherein the machine learning model is trained using deep learning techniques and the activity detection module detects starting conditions for data extraction based on the trained model.

Claim 9. A computer system for automatically capturing information from audio data and computer operating context, comprising: a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a note-taking application to provide the extracted text and salient patterns to a user.

Claim 10. The system of claim 9, wherein the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

Claim 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 speech recognition and pattern detection modules; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

Claim 12. The method of claim 11, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms and the speech recognition module uses deep learning techniques to process the audio data.

Claim 13. A computer-readable medium having computer-executable instructions for performing the method of claim 11, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

Claim 14. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

Claim 15. A method for training the speech recognition module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the speech recognition module.

Claim 16. The method of claim 15, wherein the machine learning model is trained using natural language processing techniques and the speech recognition module uses the trained model to process the audio data.

Claim 17. 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; a pattern detection module to identify salient patterns; and a note-taking application to provide the extracted text and salient patterns to a user.

Claim 18. The system of claim 17, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses deep learning techniques to process the audio data.

Claim 19. 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; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

Claim 20. The method of claim 19, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, and the speech recognition module uses natural language processing techniques to process the audio data.

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

Claim 2. The 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 deep learning techniques to process the audio data.

Claim 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; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

Claim 4. The method of claim 3, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, and the speech recognition module uses natural language processing techniques to process the audio data.

Claim 5. A computer-readable medium having computer-executable instructions for performing the method of claim 3, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

Claim 6. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

Claim 7. A method for training the activity detection module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the activity detection module.

Claim 8. The method of claim 7, wherein the machine learning model is trained using deep learning techniques and the activity detection module detects starting conditions for data extraction based on the trained model.

Claim 9. A computer system for automatically capturing information from audio data and computer operating context, comprising: a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a note-taking application to provide the extracted text and salient patterns to a user.

Claim 10. The system of claim 9, wherein the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

Claim 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 speech recognition and pattern detection modules; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

Claim 12. The method of claim 11, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms and the speech recognition module uses deep learning techniques to process the audio data.

Claim 13. A computer-readable medium having computer-executable instructions for performing the method of claim 11, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

Claim 14. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

Claim 15. A method for training the speech recognition module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the speech recognition module.

Claim 16. The method of claim 15, wherein the machine learning model is trained using natural language processing techniques and the speech recognition module uses the trained model to process the audio data.

Claim 17. 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; a pattern detection module to identify salient patterns; and a note-taking application to provide the extracted text and salient patterns to a user.

Claim 18. The system of claim 17, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses deep learning techniques to process the audio data.

Claim 19. 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; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

Claim 20. The method of claim 19, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, and the speech recognition module uses natural language processing techniques to process the audio data.

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

2. The 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 deep learning techniques to process the audio data.

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; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

4. The method of claim 3, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, and the speech recognition module uses natural language processing techniques to process the audio data.

5. A computer-readable medium having computer-executable instructions for performing the method of claim 3, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

6. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

7. A method for training the activity detection module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the activity detection module.

8. The method of claim 7, wherein the machine learning model is trained using deep learning techniques and the activity detection module detects starting conditions for data extraction based on the trained model.

9. A computer system for automatically capturing information from audio data and computer operating context, comprising: a speech recognition module to process the audio data; a pattern detection module to identify salient patterns; and a note-taking application to provide the extracted text and salient patterns to a user.

10. The system of claim 9, wherein the speech recognition module uses natural language processing techniques to process the audio data and identify salient patterns.

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 speech recognition and pattern detection modules; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

12. The method of claim 11, wherein the activity detection module detects starting conditions for data extraction based on machine learning algorithms and the speech recognition module uses deep learning techniques to process the audio data.

13. A computer-readable medium having computer-executable instructions for performing the method of claim 11, wherein the instructions are stored on the medium and executed by a computer processor to capture information from audio data and computer operating context.

14. The system of claim 1, further comprising a user interface to display the extracted text and salient patterns to a user, and a storage device to store the extracted information.

15. A method for training the speech recognition module of claim 1, comprising: providing a dataset of labeled audio data and computer operating context; training a machine learning model using the dataset; and deploying the trained model in the speech recognition module.

16. The method of claim 15, wherein the machine learning model is trained using natural language processing techniques and the speech recognition module uses the trained model to process the audio data.

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

18. The system of claim 17, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses deep learning techniques to process the audio data.

19. 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; providing the extracted text and salient patterns to a note-taking application; and displaying the extracted information to a user.

20. The method of claim 19, wherein the activity detection module detects starting conditions for data extraction based on audio data and computer operating context, and the speech recognition module uses natural language processing techniques to process the audio data.

Tire bomb, guys don't be stingy to buy. 👍🛞🫵

Excellent tires, price-quality 💯👍

Excellent tire, soft and fresh, 24, balances well

Everything is fine so far

Unfortunately, the user did not write a comment on their review.