RESUMO
OBJECTIVE: Nearly 30,000 individual inquiries are answered annually by the telephone cancer information service (CIS, KID) of the German Cancer Research Center (DKFZ). The aim was to develop a tool for evaluating these calls, and to support the complete counseling process interactively. METHODS: A novel software tool is introduced, based on a structure similar to a music score. Treating the interaction as a "duet", guided by the CIS counselor, the essential contents of the dialogue are extracted automatically. For this, "trained speech recognition" is applied to the (known) counselor's part, and "keyword spotting" is used on the (unknown) client's part to pick out specific items from the "word streams". The outcomes fill an abstract score representing the dialogue. RESULTS: Pilot tests performed on a prototype of SACA (Software Assisted Call Analysis) resulted in a basic proof of concept: Demographic data as well as information regarding the situation of the caller could be identified. CONCLUSION: The study encourages following up on the vision of an integrated SACA tool for supporting calls online and performing statistics on its knowledge database offline. PRACTICE IMPLICATIONS: Further research perspectives are to check SACA's potential in comparison with established interaction analysis systems like RIAS.
