Abstract: Techniques for monitoring and improving emotional well-being of an employee are described. Stream of audio data corresponding to a call between an employee and a customer may be received. One or more acoustic features and/or audio feature data may be generated from the audio data. Word embedding data corresponding to the audio data may be generated. An employee experience score may be generated using a machine learning (ML) model, word embedding data, and the one or more acoustic features, where the score corresponds to an experience level of the first speaker during the call with the second speaker. Based on the score, an action may be caused to be performed. In some embodiments, one or more notifications may be generated based on data related to the audio data, where at least notification is configured to improve an experience level for the first speaker.

Abstract: Techniques for monitoring and improving emotional well-being of an employee are described. Stream of audio data corresponding to a call between an employee and a customer may be received. One or more acoustic features and/or audio feature data may be generated from the audio data. Word embedding data corresponding to the audio data may be generated. An employee experience score may be generated using a machine learning (ML) model, word embedding data, and the one or more acoustic features, where the score corresponds to an experience level of the first speaker during the call with the second speaker. Based on the score, an action may be caused to be performed. In some embodiments, one or more notifications may be generated based on data related to the audio data, where at least notification is configured to improve an experience level for the first speaker.