Whose Line Is It Anyway? Creating AI That Accurately Separates Voices on Sales Calls

To attack this problem, our research team developed a patent-pending framework that uses Deep Learning to automatically generate a "voice fingerprint" for each sales rep using a combination of vocal characteristics. During the sales call itself, we cluster the audio signals based on those characteristics with each cluster representing a speaker. The voice fingerprints we stored play a crucial role not only in associating each speaker with the right cluster, but in the clustering process itself: the models we trained with the fingerprints allow us to learn and apply mathematical transformations to the audio, which render the differences between different speakers more distinct. See the before and after graphs below.