Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of audio files. Each audio file in the set of audio files includes audio from an audio call. The program further truncates each audio file in the set of audio files to a defined call length. For each audio call in the set of audio calls, the program also receives a transcript of the audio call based on the audio file of the audio call. For each audio call in the set of audio calls, the program further uses the transcript of the audio call as input to a machine learning model for the machine learning model to predict a category from a plurality of categories that is associated with the audio call.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of audio files. Each audio file in the set of audio files includes audio from an audio call. The program further truncates each audio file in the set of audio files to a defined call length. For each audio call in the set of audio calls, the program also receives a transcript of the audio call based on the audio file of the audio call. For each audio call in the set of audio calls, the program further uses the transcript of the audio call as input to a machine learning model for the machine learning model to predict a category from a plurality of categories that is associated with the audio call.

Abstract: The present invention relates to hair treatment compositions and methods. More particularly, the invention relates to hair treatment compositions comprising lipids and creatine. The hair treatment compositions of the present invention may be used to improve the tensile properties of hair, such as hair elasticity and strength.