Transcriptions of phone calls hold significant value in sales, customer service, healthcare, law enforcement, and more. However, analyzing recorded conversations can be a time-consuming process, especially for complex dialogues. In Microsoft Dynamics 365 Sales, a novel system, named GPT-Calls, is applied for efficient and accurate topic-based call segmentation. GPT-Calls comprises offline and online phases. In the offline phase, the system leverages a GPT model to generate synthetic sentences and extract anchor vectors for predefined topics. This phase, performed once on a given topic list, significantly reduces the computational burden. The online phase scores the similarity between the transcribed conversation and the topic anchors from the offline phase, followed by time domain analysis to group utterances into segments and tag them with topics. The GPT-Calls scheme offers an accurate and efficient approach to call segmentation and topic extraction, eliminating the need for labeled data. It is a versatile solution applicable to various industry domains. GPT-Calls operates in production under Dynamics 365 Sales Conversation Intelligence, applied to real sales conversations from diverse Dynamics 365 Sales tenants, streamlining call analysis, and saving time and resources while ensuring accuracy and effectiveness.
|Title of host publication
|CIKM 2023 - Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
|Association for Computing Machinery
|Number of pages
|Published - 21 Oct 2023
|32nd ACM International Conference on Information and Knowledge Management, CIKM 2023 - Birmingham, United Kingdom
Duration: 21 Oct 2023 → 25 Oct 2023
|International Conference on Information and Knowledge Management, Proceedings
|32nd ACM International Conference on Information and Knowledge Management, CIKM 2023
|21/10/23 → 25/10/23
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