The AI Sarcasm Detection Protocol (ASDP) proposed in this RFC is a framework for detecting sarcasm in AI systems. The protocol consists of two main components: training data and a sarcasm detection algorithm.
To train an AI system to detect sarcasm, a large dataset of sarcastic and non-sarcastic language samples must be collected. This dataset should be diverse and representative of the language and context in which the AI system will be used.
The dataset should be labeled to indicate which language samples are sarcastic and which are not. The labels can be either binary (sarcasm or not sarcasm) or graded (e.g., a score indicating the degree of sarcasm).
Once the dataset is prepared, the AI system can be trained using natural language processing (NLP) techniques. Popular NLP techniques for sarcasm detection include machine learning algorithms such as Support Vector Machines (SVMs), Naive Bayes, and Deep Learning models.
The sarcasm detection algorithm takes in a text input and returns a binary classification indicating whether the text is sarcastic or not. The algorithm typically consists of several processing steps, including tokenization, feature extraction, and classification.
The text input is split into individual words or tokens. This istypically done using a tokenizer, such as the NLTK library in Python.
Features that are indicative of sarcasm are extracted fromthe tokens. These features can include linguistic patterns (e.g., the use ofexaggeration, irony, or understatement), contextual cues (e.g., the use of quotationmarks or emoticons), and sentiment analysis (e.g., detecting a discrepancybetween the sentiment of the words and the sentiment of the overall message).
The extracted features are then used to classify the input as sarcastic or not sarcastic. This can be done using a variety of machine learning algorithms, as mentioned above.
HTTP/2 [RFC 9113
] can be used to transport sarcasm detection requests and responses between the AI system and client applications. Additionally, the results of sarcasm detection can be logged using the syslog protocol [RFC 5424
] or the structured data format.