Reifenbewertungen Continental ContiSportContact 6 97

Auf einem Rallye-Fahrzeug, wurde auf einem Testgelände mit verschiedenen Bedingungen gefahren. Das ist eine tolle Schiene, nass, trocken, Sand und sogar auf Armierungspenten getestet, um den Seitenwind zu prüfen.

Ich denke, es ist die beste Zivilreifen für den Stadtverkehr.

Ich habe mich nicht geirrt ! Die sportcontact 5 auf nasser Straße waren nicht so toll und das Aquaplaning war auch nicht optimal, aber alle diese Mängel fehlen mir auf der sportcontact 6 ! Ich empfehle diese Schiene zu ihrem Preis ! Sie sind weich und stabil und funktionieren auch auf nasser und trockener Straße !

Die neue Reifenmarke ist eine wunderbare Alternative zum SportContact 5P. Das Profil 35 bietet hervorragende Reifenfestigkeit, perfekte Bremsleistung auf trockener und nasser Straße und ein hervorragendes Reaktionsvermögen. Es gibt keine Vibrationen, die Reifen sind sehr komfortabel, auch für Low-Profile-Reifen. Die Reifen sind sehr leise

Ich kaufe bereits den siebten Sattel, nicht nur für mein eigenes Auto! Die Reifen sind top, mein Manager, Apitikeev Igor, bearbeitet die Bestellungen schnell, nimmt sogar am Wochenende Anrufe entgegen und informiert mich in der Freizeit über den Status der Bestellung. Sein Ansatz ist absolut richtig! Leider kann ich das nicht von der Filiale in Rostov am Don, Prospekt Korole

Das ist kein Gummi, sondern ein Meisterwerk. Ich hatte in meinem Leben viele Pirelli, Yokohama, Goodyear, aber diese sind die besten. Die 245×35 R20 haben sich als WEICHER erwiesen als meine 6 Jahre alten 17-Zoll-Räder. Die Black-Chili-Mischung ist die Bombe. Sie sind unglaublich leise. Die leiseste Reifen, die ich je hatte. Bei dem Zikk-Profil dachte ich, sie würden auf jeden Fall Lärm machen. Aber alles ist viel angenehmer. Mein Auto ist ein Lexus ES 7. Generation.

Ich bin enttäuscht. Die erste CONTI-Reifen, die mich enttäuscht hat. Größe 285/35 ZR R22 100Y, Audi Q7. Akustischer Komfort auf 2 Punkte! Hintergrundgeräusch auf der ganzen Fahrt ein merkbarer metallischer Knirscher, der sich mit zunehmender Geschwindigkeit verstärkt. Bei 70 km/h noch verträ

Sehr gute Reifen, leise und nicht laut. Einziger Nachteil: diese Reifen sind Selbstschraubern sehr zugetan. Bisher waren es Continental, da gab es kein Problem mit Selbstschraubern. Vielleicht ist es ein Zufall. Derzeit möchte ich meinen Set verkaufen und einen neuen kaufen. Anscheinend werde ich sie wieder kaufen, da es bei den Reifengrößen 295/30/22 und

Ich habe zwei Räder aus Portugal für 2023-2024 erhalten. Zwei Räder aus Tschechien für 2025. Die Räder sind nicht nur durch das Baujahr, sondern auch durch ihr Aussehen unterschiedlich. Portugal ist deutlich steifer. Mehr als hunderttausend für Räder mit einer Geschwindigkeitsbegrenzung von 300 km/h zu bezahlen und eine zusammengewürfelte "Mischung" zu erhalten, ist inakzeptabel. Sie müssen eine engere Verbindung zum Lager haben. Ich bereue, dass ich mich mit Ihrem Unternehmen in Verbindung gesetzt habe.

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

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

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

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

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

Bisher ist alles mehr als zufriedenstellend - sowohl das Verhalten bei hoher Geschwindigkeit, als auch die Handhabung im Allgemeinen und bei starkem Regen und der Lärmpegel.

Gute qualitativ hochwertige Reifen