Computational modelling of speech data integration to assess interactions in B2B sales calls

Vered Silber-Varod, A Lerner, N Carmi, D Amit, Y Guttel, C Orlob, O Allouche

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرمنشور من مؤتمرمراجعة النظراء

ملخص

The business sector now recognizes the value of
Conversation Intelligence in understanding patterns, structures
and insights of authentic conversation. Using machine learning
methods, companies process massive amount of data about
conversation content, vocal features and even speaker body
gestures of spoken conversations. This study is a Work-inProgress (WIP), aimed to modeling the dynamics between sales representatives and customers in business-to-business (B2B) sales calls, by relying solely on the acoustic signal. To this end, we analyze 358 sales calls at the Discovery phase. To model the conversations, we compute a basic set of acoustic features: Talk proportions, F0, intensity, harmonics-to-noise ratio (HNR), jitter, and shimmer. The plots of each acoustic feature reveal the interactions and common behavior across calls, on one hand, and within calls, on the other. The study demonstrates that using delta metrics to assess the interactions leads to new insights.
اللغة الأصليةالإنجليزيّة
عنوان منشور المضيفProceedings of the IEEE 5th International Conference on Big Data Intelligence and Computing
الصفحات152-157
عدد الصفحات6
حالة النشرنُشِر - 2019
الحدثThe 5th IEEE International Conference on Big Data Intelligence and Computing: DataCom 2019 - Kaohsiung, تيوان
المدة: ١٨ نوفمبر ٢٠١٩٢١ نوفمبر ٢٠١٩

!!Conference

!!ConferenceThe 5th IEEE International Conference on Big Data Intelligence and Computing
الدولة/الإقليمتيوان
المدينةKaohsiung
المدة١٨/١١/١٩٢١/١١/١٩

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