ComParE 2023 HealthCall Corpus (HC-C)

This is a subset (audio-only) of the HealthCall corpus, provided by Claude Montacié and colleagues. It is based on real audio interactions between call centre agents and customers who call to solve a problem or to request information. This corpus is designed to study natural spoken conversations and to predict Customer Relationship Management (CRM) annotations made by human agents from various vocal interaction, audio, and linguistic features. The corpus consists of 13,409 chunks of spoken conversations, each lasting 30 seconds. Each conversation was recorded on two separate and distinct audio channels: the first channel corresponds to the customer’s audio, and the second corresponds to the agent’s audio. More information can be found here.