luis.ai vs api.ai vs wit.ai之间的比较？

Question

有没有人知道三者之间的具体差异和特点，或者如果有更多的功能/更灵活的使用作为开发人员？

Answer 1

wit.aivsapi.aivsluis.ai

╔══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ 
║             wit.ai vs api.ai vs luis.ai             ║ 
╠══════╦════════════════════════════════════╦═════════════════════════════════════════════╦════════════════════════════════════╣ 
║ S.No ║    Wit.ai    ║     Api.ai     ║    Luis.ai    ║ 
╠══════╬════════════════════════════════════╬═════════════════════════════════════════════╬════════════════════════════════════╣ 
║ 1 ║ Wit.ai API is completely free  ║ Api.ai Has a paid enterprise option   ║ LUIS is in beta and free to use ║ 
║  ║ with no limitations on    ║ which allows for this to be run on a  ║ 10K transactions per month   ║ 
║  ║ request rates.      ║ private cloud internally and more   ║ and up to 5 requests per second ║ 
║  ║         ║ from their services team., After google  ║ for each account.     ║ 
║  ║         ║ acquisition they are providing free   ║         ║ 
║  ║         ║ services by integrating google cloud  ║         ║ 
║  ║         ║ services.         ║         ║ 
╠══════╬════════════════════════════════════╬═════════════════════════════════════════════╬════════════════════════════════════╣ 
║ 2 ║ Provides a nice combination  ║ Speech to Text and Text to Speech   ║ LUIS uses machine learning   ║ 
║  ║ of both voice recognition and  ║ capabilities, along with machine   ║ based methods to analyze   ║ 
║  ║ machine learning for developers. ║ learning.         ║ sentences. To perform machine  ║ 
║  ║         ║            ║ learning, LUIS breaks an   ║ 
║  ║         ║            ║ utterance into "tokens".   ║ 
╠══════╬════════════════════════════════════╬═════════════════════════════════════════════╬════════════════════════════════════╣ 
║ 3 ║ Has two main elements to it  ║ Support of Intents, Entities, actions  ║ Supports Intents, Entities   ║ 
║  ║ that you set up within your  ║ and one key focus area is its “Domains”. ║ and actions.      ║ 
║  ║ app – intents and entities.  ║            ║         ║ 
║  ║ Actions are separated to   ║            ║         ║ 
║  ║ use as a combined operations.  ║            ║         ║ 
╠══════╬════════════════════════════════════╬═════════════════════════════════════════════╬════════════════════════════════════╣ 
║ 4 ║ Has pre-build entities like  ║ Has pre-build entities like @sys.date,  ║ Has pre-build entities    ║ 
║  ║ temperature, number, URLs,   ║ @sys.color, @sys.unit-currency… etc.  ║ builtin.intent.alarm,    ║ 
║  ║ emails, duration… etc.    ║            ║ builtin.intent.calendar,   ║ 
║  ║         ║            ║ builtin.intent.email… etc.   ║ 
╠══════╬════════════════════════════════════╬═════════════════════════════════════════════╬════════════════════════════════════╣ 
║ 5 ║ Doesn’t have integration module ║ Has integration module to connect   ║ Has integration to Microsoft  ║ 
║  ║ to directly communicating with  ║ directly to Facebook messenger and   ║ Azure and other services, can be ║ 
║  ║ Facebook messenger or other  ║ other messenger api’s. Has support for  ║ deployable in any supported  ║ 
║  ║ messenger APIs. but has web  ║ deploying in to heroku server, enterprise ║ servers.       ║ 
║  ║ service api to hook services.  ║ paid environment.       ║         ║ 
╠══════╬════════════════════════════════════╬═════════════════════════════════════════════╬════════════════════════════════════╣ 
║ 6 ║ Early in 2015, joined Facebook  ║ Created by a team who built personal  ║ LUIS was introduced together with ║ 
║  ║ and opened up the entire platform ║ assistant app for major mobile platforms ║ Microsoft Bot Framework and Skype ║ 
║  ║ to be free for both public and  ║ with speech and text enabled conversations. ║ Developer Platform which can be ║ 
║  ║ private instances.     ║ acquired by google (sept 2016).    ║ used to create Skype Bots.   ║ 
╠══════╬════════════════════════════════════╬═════════════════════════════════════════════╬════════════════════════════════════╣ 
║ 7 ║ Wit.ai API for developers of iOS, ║ Api.ai has SDKs for Android, iOS,   ║ LUIS allow building applications ║ 
║  ║ Android, Node.js, Raspberry Pi, ║ the Apple Watch, Node.js, Cordova,   ║ by using the LUIS web interface. ║ 
║  ║ Ruby, Python, C, Rust and   ║ Unity, C#, Xamarin, Windows Phone,   ║ No coding needed other than the ║ 
║  ║ Windows Phone. It even    ║ Python and JavaScript. It also can be  ║ ability to interpret and use the ║ 
║  ║ has a JavaScript plugin for  ║ integrated with Amazon’s Echo and   ║ returned JSON in application.  ║ 
║  ║ front end developers.    ║ Microsoft’s Cortana.      ║ It is also possible to use the  ║ 
║  ║         ║            ║ LUIS REST API for     ║ 
║  ║         ║            ║ automation of applications.  ║ 
╚══════╩════════════════════════════════════╩═════════════════════════════════════════════╩════════════════════════════════════╝ 

更新：现在 API.AI是Dialogflow。 Learn more here.

Answer 2

这个blogpost对Luis，Wit.ai，Api.ai，Amazon Alexa和IBM Watson服务进行了非常好的分析和比较。它还有一个很好的背景，就是你为什么想要首先构建一个对话式的机器人，以及随之而来的一些挑战。它是由YumiBot（一种可为您提供应用程序开发报价的机器人）背后的人写的。

的一般要点是，Wit.ai和路易斯是，如果你尝试，只是想要得到的东西出来免费的绝佳选择。 Api.ai有一个伟大的服务和用户体验，但不是免费的。与一样，IBM Watson，后者的价格更多用于企业工作。 Alexa的 API是伟大的，但只适用于Alexa（但鉴于他们有一个巨大的用户群，不是一个坏的交易）。

他们的建议也不要过分依赖一个供应商：

我们建议您存储在自己的代码库以结构化方式所需要的模型的所有数据。所以，以后你可以从零开始重新训练模型，甚至可以根据需要更改语言理解提供者。你只是不想处于公司关闭服务的情况下，而你完全没有准备好。你还记得Parse吗？

我希望这会有所帮助！我认为做出选择的最佳方式就是试试这些服务。鉴于它们中的很多仍在开发中，并且增加了功能/更改定价模型，您应该尝试使用特定的用例来查看它们，并查看哪一个可以将您带到最需要的地方。

Answer 3

这个问题的一个方面是这些工具在理解自然语言方面有多高效。在刚刚发布的最新基准测试中，我们测试了Alexa（亚马逊），SiriKit（苹果），Luis（微软）和API.ai（Google）的内置自然语言引擎。

我们测试了他们理解天然问题的能力，例如“找到我可以去参加午餐会的沙拉吧”，“订购6人出租车”以及其他326个查询。

总体结论是所有的解决方案都不完善。

更准确地说，它们的响应都具有相似的噪声水平（精度在60％到90％之间），但是它们可以支持的语言宽度存在显着差异。从这个角度来看，Luis的表现最差：在我们测试的每个用例上，它理解的查询少于14％。 API。ai执行得更好，虽然不是很可靠：它可以理解我们测试的查询的0％到80％，这取决于用例。对于Alexa（42％和82％召回）和Siri（61％召回），可以观察到召回的最高水平。

更多细节，而这些成果背后的原始数据可以在我们的博客文章中找到，Benchmarking Natural Language Understanding Systems

Answer 4

我们最近published an evaluation study of seven NLU API-enabled services：API.ai，亚马逊莱克斯，微软LUIS，IBM沃森对话，wit.ai， Recast.ai和Snips.ai。

一个我们的研究结果小结：

• IBM沃森意图检测是最好的，特别是在较小的训练数据（尽管当超过2000个样本的培训上的差异是无法区分）。
• API.AI是免费的，足够大的培训集的性能与IBM Watson和Microsoft LUIS相匹配。
• 在我们的测试中，Microsoft LUIS的工作速度明显快于其他人。 wit.ai与上述三者相比，性能和响应时间稍差，但它是免费的，它提供了最好的语言覆盖（约50种语言）。
• 亚马逊Lex的API限制相当严格（训练集大小限制为200K符号，这可能不足以达到多意图助理的良好意图检测质量;也需要所有训练语句由实体标记，其中如果需要 复杂编制的数据集。

Answer 5

在我看来路易斯更为稳健，并且可以在不同的语言中提取实体。 我在api.ai测试和荷兰并没有为我工作。英语只有他们中的任何一个都可以，但如果您需要支持更多的语言，那么在使用一种服务之前，最好先测试一下这些语言。 Bing语音文本可以我认为要获得更强大的解决方案，您需要另一种可清除语音和噪音的微软服务。