The intent recognition is an essential algorithm of any conversational AI application. It is responsible for the classification of an input message into meaningful classes. In many bot development platforms, we can configure the NLU pipeline. Several intent recognition services are currently available as an API, or we choose from many open-source alternatives. However, there is no comparison of intent recognition services and open-source algorithms. Many factors make the selection of the right approach to the intent recognition challenging in practice. In this paper, we suggest criteria to choose the best intent recognition algorithm for an application. We present a dataset for evaluation. Finally, we compare selected public NLU services with selected open-source algorithms for intent recognition.
翻译：目的识别是任何对话性 AI 应用程序的基本算法。 它负责将输入信息分类为有意义的类别。 在许多机器人开发平台中, 我们可以配置 NLU 管道。 目前有几个意向识别服务可以作为 API 提供, 或者我们从许多开放源的替代办法中选择。 但是, 意向识别服务和开放源的算法没有比较。 许多因素使得选择正确方法对意图识别具有挑战性。 在本文中, 我们建议选择一个应用程序的最佳意向识别算法的标准。 我们为评估提供一个数据集。 最后, 我们将选定的公共 NLU 服务与选定的公开源算法进行比较, 以便识别意图。
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