SYSTEMS AND METHODS FOR AUTOMATICALLY CONFIGURING TRAINING DATA FOR TRAINING MACHINE LEARNING MODELS OF A MACHINE LEARNING-BASED DIALOGUE SYSTEM INCLUDING SEEDING TRAINING SAMPLES OR CURATING A CORPUS OF TRAINING DATA BASED ON INSTANCES OF TRAINING DATA IDENTIFIEDAS ANOMALOUS

A system and method for improving a machine learning-based dialogue system includes: sourcing a corpus of raw machine learning training data from sources of training data based on a plurality of seed training samples, wherein the corpus of raw machine learning training data comprises a plurality of distinct instances of training data; generating a vector representation for each distinct instance of training data; identifying statistical characteristics of the corpus of raw machine learning training data based on a mapping of the vector representation for each distinct instance of training data; identifying anomalous instances of the plurality of distinct instances of training data of the corpus of raw machine learning training data based on the identified statistical characteristics of the corpus; and curating the corpus of raw machine learning training data based on each of the instances of training data identified as anomalous instances.