轮胎评价 Continental ContiPremiumContact 5. Страница 4 634

**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.

**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 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, including audio data and user input, and provides the extracted information to the notetaking application.

2. The system of claim 1, wherein the speech recognition module uses machine learning algorithms to identify salient patterns and provide the extracted information to the user.

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; and providing the extracted text and salient patterns to a notetaking application, wherein the method uses natural language processing to identify salient patterns.

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

5. The system of claim 1, wherein the activity detection module uses a machine learning algorithm to detect starting conditions for data extraction based on the computer operating context, including audio data and user input.

6. A non-transitory computer-readable medium storing instructions for executing 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 providing the extracted text and salient patterns to a notetaking application.

7. The method of claim 3, wherein the speech recognition module uses deep learning to identify salient patterns and provide the extracted information to the user.

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

9. The computer system of claim 1, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context, including audio data and user input, and provides the extracted information to the notetaking application.

10. A method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and computer operating context; detecting starting conditions for data extraction using an activity detection module; processing the audio data using a speech recognition module; and providing the extracted text and salient patterns to a notetaking application, wherein the method uses natural language processing to identify salient patterns.

**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 a notetaking application to provide the extracted text and salient patterns 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 based on the computer operating context, including audio data and user input.

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; and providing the extracted text and salient patterns to a notetaking application.

4. The method of claim 3, wherein the speech recognition module uses deep learning to identify salient patterns and provide the extracted information to the user.

5. A non-transitory computer-readable medium storing instructions for executing a method for automatically capturing information from audio data and computer operating context, comprising: receiving audio data and computer operating context; detecting starting conditions for data extraction; processing the audio data using speech recognition; and providing the extracted text and salient patterns to a notetaking application.

6. The system of claim 1, wherein the notetaking application uses natural language processing to provide the extracted text and salient patterns to the user.

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

8. The method of claim 7, wherein the activity detection module detects starting conditions for data extraction based on the computer operating context, including audio data and user input.

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

10. The computer system of claim 1, wherein the speech recognition module uses machine learning to identify salient patterns and provide the extracted information to the user.

這已經是第二輛安裝了這種輪胎的汽車。很好，非常好。如果不是有一個但是...，在第三個季度，輪胎開始變硬，高速公路上會很吵。在不平的路面上會非常顫抖，想要檢查一下懸掛系統。降低胎壓並不能幫助。之前在Peugeot 308上使用，現在在Duster上使用。這兩輛車完全不同，但是輪胎的性能卻是一樣的。我只推薦使用兩年。

在各方面都是不错的轮胎，我寻找的是相对较软的轮胎，这款轮胎符合我的期望。驾驶起来非常舒适。在使用过程中，无论是不同的路面还是铁轨，都没有出现损坏，当然是指在合理的速度下。唯一不满意的是轮胎的磨损比较快，考虑到价格，这样的使用寿命有点太短了。

优异的沥青路面轮胎，无论是在湿润还是干燥的道路上，抓地力都非常出色。在操控性、抓地力和制动能力方面，给它五星，但在耐磨性方面，只能给三星，因为在激进的驾驶方式下，胎面真的很快就会磨损。在雨天的土路上行驶比较困难，如果遇到泥土路面，几乎无法行驶。在良好的平整沥青路面上，表现完美，没有任何抱怨。行驶38,000公里后，轮胎基本上已经报废，剩余胎面深度只有1毫米。

在价格合理的时候购买的。湿滑和干燥的路面上操控性很好。水洼（水滑）效果很好。在上面跑了两个季节。随着磨损，噪音会增加。很好的轮胎

公路舒适柔软的轮胎
如果不是很锋利的卵石路，也还不错，但是对于锋利的岩石很容易被刺破或穿孔。

continental ContiPremiumContact 5 225/65 R17 102V 软胎，完全无噪音，经过高速公路和城市道路测试。我的评分：5分。

尺寸：205/55R16。非常好的轮胎，推荐购买，但很遗憾地发现，没有这种尺寸的轮胎可供购买，可能是供阿瓦兹公司运营用的。经销商进行了保证期内的维修，维修耗时16天，回到家里，距离经销商有300公里，发现一个轮胎被更换，轮胎严重损耗，看起来可能是发生了胎破坏，

我在网上看了许多关于汽车轮胎的评论后，决定试试这款轮胎。它是一款俄罗斯产的轮胎，价格便宜，售价5元/cp。事实上，这款轮胎是生产商在车上将轮胎送货的状态。经过3个季节的使用，轮胎表现还算不错。它可以承受正常的路况，但并不软亦不安静。它可以正常

<<个体差异>>很好的轮胎，路面抓握好，高速转弯时稳定度很好，胎侧高。驶入不平路面，胎面能很好地吞噬振动。与护壁接触且不容易损坏胎面和轮毂。非常安静，胎面轻软。价格与质量相符。