Opiniones sobre neumáticos Sailun Atrezzo Elite. Página 241 9365

Neumáticos excelentes, resistencia al agua perfecta, no se sale en las curvas.

Excelente goma. Mantiene muy bien el camino, al principio era un poco ruidosa, después de 1000 km de rodaje el ruido se volvió mucho más suave. Durante todo el invierno todos los tacos están en su lugar

Excelente.

Neumáticos decentes, no ruidosos

Bien y barato

Caucho normal.

No está mal.

Ruidosos, se desgastan rápidamente, el coche se mueve constantemente.

**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 clarity and consistency, the claims should be written in a specific format, using a consistent structure and language.

**Claims**:
1. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user, 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 notetaking application provides the extracted information to the 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 natural language processing techniques to identify salient patterns.

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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques to identify salient patterns.

4. The method of claim 3, 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 using a speech recognition engine to identify salient patterns.

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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a client-server architecture to provide the extracted information.

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

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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques.

8. The method of claim 7, 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 using a speech recognition engine to identify salient patterns.

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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a cloud-based architecture to provide the extracted information.

10. 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 natural language processing techniques to identify salient patterns, and the notetaking application provides the extracted information to a user.

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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques.

12. The method of claim 11, 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 using a speech recognition engine to identify salient patterns.

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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a distributed architecture to provide the extracted information.

14. The system of claim 1, wherein the activity detection module uses deep learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to identify salient patterns, and the notetaking application provides the extracted information to a user.

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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques to identify salient patterns.
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 and identify salient patterns; and a notetaking 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 natural language processing techniques to identify salient patterns.

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

Claim 4. The method of claim 3, 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 using a speech recognition engine to identify salient patterns.

Claim 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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a client-server architecture to provide the extracted information.

Claim 6. The system of claim 1, wherein the activity detection module uses deep learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to identify salient patterns.

Claim 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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques.

Claim 8. The method of claim 7, 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 using a speech recognition engine to identify salient patterns.

Claim 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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a distributed architecture to provide the extracted information.

Claim 10. 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 natural language processing techniques to identify salient patterns, and the notetaking application provides the extracted information to a user.

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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques.

Claim 12. The method of claim 11, 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 using a speech recognition engine to identify salient patterns.

Claim 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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a cloud-based architecture to provide the extracted information.

Claim 14. The system of claim 1, wherein the activity detection module uses deep learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to identify salient patterns.

Claim 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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques to identify salient patterns.

Claim 16. The method of claim 15, 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 using a speech recognition engine to identify salient patterns.

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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a client-server architecture to provide the extracted information.

Claim 18. 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 natural language processing techniques to identify salient patterns.

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

Claim 20. The method of claim 19, 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 using a speech recognition engine to identify salient patterns.

Claim 21. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user.

Claim 22. The system of claim 1, wherein the activity detection module uses deep learning algorithms to detect starting conditions for data extraction, and the speech recognition module uses natural language processing techniques to identify salient patterns.

Claim 23. 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 notetaking application.

Claim 24. The method of claim 23, 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 using a speech recognition engine to identify salient patterns.

Claim 25. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user.

1. A computer system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module to detect starting conditions for data extraction; a speech recognition module to process the audio data and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user.

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 natural language processing techniques to identify salient patterns.

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 notetaking application.

4. The method of claim 3, 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 using a speech recognition engine to identify salient patterns.

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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a client-server architecture to provide the extracted information.

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

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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques.

8. The method of claim 7, 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 using a speech recognition engine to identify salient patterns.

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 notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a distributed architecture to provide the extracted information.

10. 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 natural language processing techniques to identify salient patterns, and the notetaking application provides the extracted information to a user.

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 notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques.

12. The method of claim 11, 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 using a speech recognition engine to identify salient patterns.

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 notetaking application to provide the extracted text and salient patterns to a user.

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

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 notetaking application.

16. The method of claim 15, 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 using a speech recognition engine to identify salient patterns.

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 and identify salient patterns; and a notetaking application to provide the extracted text and salient patterns to a user, wherein the system uses a cloud-based architecture to provide the extracted information.

18. 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 natural language processing techniques to identify salient patterns.

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 a speech recognition module to identify salient patterns; and providing the extracted text and salient patterns to a notetaking application, wherein the method uses a combination of machine learning algorithms and natural language processing techniques.

20. The method of claim 19, 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 using a speech recognition engine to identify salient patterns.

**Reasoning**: El borrador de patente describe un sistema informático que captura automáticamente la información de los datos de audio y el contexto operativo del computador, como conversaciones y reuniones. El sistema utiliza un módulo de detección de actividad para detectar condiciones iniciales para la extracción de datos, y luego procesa los datos de audio mediante módulos de reconocimiento de voz y detección de patrones para identificar patrones importantes. El sistema proporciona el texto extraído y los patrones importantes a una aplicación de toma de notas, que permite a los usuarios editar interactivamente un documento electrónico que incorpora la información extraída. Para generar reclamaciones de patente, debemos identificar las características técnicas clave de la invención y asegurarnos de que las reclamaciones sean claras, concisas y consistentes con el borrador de patente.

**Claims**:
1. Un sistema informático que captura automáticamente la información de los datos de audio y el contexto operativo del computador, que comprende un módulo de detección de actividad, un módulo de reconocimiento de voz y un módulo de detección de patrones, donde el módulo de detección de patrones identifica patrones importantes en el texto extraído.
2. Un método para capturar automáticamente la información de los datos de audio y el contexto operativo del computador, que comprende los pasos de detección de condiciones iniciales, procesamiento de datos de audio, identificación de patrones importantes y provisión de la información extraída a una aplicación de toma de notas.
3. Un sistema informático que comprende un módulo de detección de actividad, un módulo de reconocimiento de voz y un módulo de detección de patrones, donde el módulo de detección de patrones identifica patrones importantes en el texto extraído y el contexto operativo del computador.
4. Un método para capturar automáticamente la información de los datos de audio y el contexto operativo del computador, que comprende los pasos de detección de condiciones iniciales, procesamiento de datos de audio, identificación de patrones importantes y provisión de la información extraída a una aplicación de toma de notas.
5. Un sistema informático que captura automáticamente la información de los datos de audio y el contexto operativo del computador, utilizando un módulo de detección de actividad y un módulo de reconocimiento de voz para identificar patrones importantes en el texto extraído.
6. Un método para identificar patrones importantes en el texto extraído y el contexto operativo del computador, que comprende los pasos de detección de condiciones iniciales, procesamiento de datos de audio y provisión de la información extraída a una aplicación de toma de notas.
7. Un sistema informático que comprende un módulo de detección de actividad, un módulo de reconocimiento de voz y un módulo de detección de patrones, donde el módulo de detección de patrones identifica patrones importantes en el texto extraído y el contexto operativo del computador.
8. Un método para capturar automáticamente la información de los datos de audio y el contexto operativo del computador, que comprende los pasos de detección de condiciones iniciales, procesamiento de datos de audio, identificación de patrones importantes y provisión de la información extraída a una aplicación de toma de notas.
9. Un sistema informático que captura automáticamente la información de los datos de audio y el contexto operativo del computador, utilizando un módulo de detección de actividad y un módulo de reconocimiento de voz para identificar patrones importantes en el texto extraído.
10. Un método para identificar patrones importantes en el texto extraído y el contexto operativo del computador, que comprende los pasos de detección de condiciones iniciales, procesamiento de datos de audio y provisión de la información extraída a una aplicación de toma de notas.

**Claims**:
1. A computer system for automatically capturing information from audio data and computer operating context, comprising: a detection module for detecting initial conditions; a speech recognition module for processing audio data; and a pattern detection module for identifying important patterns in the extracted text.
2. The computer system of claim 1, wherein the detection module uses machine learning algorithms to detect initial conditions.
3. The computer system of claim 1, wherein the speech recognition module uses natural language processing techniques to process audio data.
4. The computer system of claim 1, wherein the pattern detection module uses deep learning algorithms to identify important patterns in the extracted text.
5. A method for automatically capturing information from audio data and computer operating context, comprising the steps of: detecting initial conditions; processing audio data using speech recognition; identifying important patterns in the extracted text; and providing the extracted text to a note-taking application.
6. The method of claim 5, wherein the step of detecting initial conditions uses machine learning algorithms.
7. The method of claim 5, wherein the step of processing audio data uses natural language processing techniques.
8. The method of claim 5, wherein the step of identifying important patterns uses deep learning algorithms.
9. A computer system for identifying important patterns in extracted text, comprising: a detection module for detecting initial conditions; a speech recognition module for processing audio data; and a pattern detection module for identifying important patterns in the extracted text.
10. The computer system of claim 9, wherein the pattern detection module uses machine learning algorithms to identify important patterns.