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Discovering Natural Language Commands in Multimodal Interfaces Arjun SrinivasanGeorgia Inst. Of Technology Atlanta, GA arjun010@gatech.eduMira Dontcheva Adobe Research Seattle, WA mirad@adobe.comABSTRACT
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01
Start by identifying the natural language commands you want to discover.
02
Understand the syntax and structure of the natural language commands.
03
Create a dataset of example sentences that demonstrate the different variations and possibilities of the commands.
04
Annotate the dataset with the corresponding intent and entities for each sentence.
05
Split the dataset into training and evaluation sets.
06
Choose a natural language processing (NLP) framework or tool to train a language model on the annotated dataset.
07
Define the architecture and parameters for the language model.
08
Train the language model using the training set.
09
Evaluate the performance of the language model using the evaluation set.
10
Fine-tune the language model if necessary.
11
Use the trained language model to predict intents and entities from new natural language commands.

Who needs discovering natural language commands?

01
Anyone developing natural language understanding systems or chatbots.
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Discovering natural language commands refers to the process of identifying and understanding commands or queries expressed in natural language, enabling systems to process and act upon them effectively.
Individuals or entities that utilize natural language processing technologies to command or interact with systems may be required to file discovering natural language commands, typically as part of regulatory or compliance frameworks.
To fill out discovering natural language commands, one must provide clear and concise examples of natural language commands used, explain the context of their use, and detail the systems they interact with.
The purpose of discovering natural language commands is to improve user-system interaction, enhance understanding of user intent, and facilitate the development of more intuitive and effective natural language processing solutions.
Information reported must include examples of natural language commands, metadata about their usage (such as frequency and context), and any relevant technical specifications regarding the systems processing these commands.
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