callssuchdataset

CallsSuchDataset is a comprehensive dataset designed to facilitate research in the field of computational linguistics, particularly in the study of direct speech acts and their linguistic properties. The dataset consists of a large collection of transcribed telephone conversations, each annotated with detailed metadata and linguistic annotations. The conversations are sourced from a variety of domains, including customer service, technical support, and general informational queries, providing a diverse and representative sample of direct speech acts.

The dataset includes annotations for speech acts, dialogue acts, and other relevant linguistic features. Speech acts are classified according to the Speech Act Theory, which categorizes utterances based on their intended effects on the listener. Dialogue acts, on the other hand, are classified based on their role in the dialogue structure, such as questions, statements, and backchannels. Additionally, the dataset provides annotations for syntactic and semantic features, such as part-of-speech tags, named entities, and dependency relations.

CallsSuchDataset is intended to support research in several areas, including dialogue systems, natural language understanding, and computational pragmatics. Researchers can use the dataset to train and evaluate models for speech act recognition, dialogue act classification, and other related tasks. The dataset is also useful for studying the linguistic properties of direct speech acts in real-world conversations.

The dataset is available for download from the CallsSuchDataset website, where researchers can access the annotated conversations, documentation, and tools for working with the data. The website also provides information on how to cite the dataset in academic publications. CallsSuchDataset is released under a Creative Commons license, allowing researchers to use and modify the data for their own purposes.