Systems and methods for intelligently curating machine learning training data and improving machine learning model performance

A method for intelligently curating machine learning training data for implementing a machine learning-based dialogue service, the method comprising:

• an machine learning-based dialogue service implemented by one or more hardware computing servers:
• constructing a corpora of machine learning test corpus that comprise a plurality of historical queries and/or historical commands test-sampled from one or more production logs of a deployed dialogue system;
• configuring one or more training data sourcing parameters to source a corpora of raw machine learning training data from the one or more sources of machine learning training data;
• obtaining, from the one or more sources of machine learning training data, the corpora of raw machine learning training data based on the one or more training data sourcing parameters;
• calculating, using the one or more hardware computing servers, one or more efficacy metrics of the corpora of raw machine learning training data;
• and
• identifying whether to train at least one machine learning classifier of the machine learning-based dialogue system based on the one or more efficacy metrics of the corpora of raw machine learning training data.

A method for intelligently curating machine learning training data for implementing a machine learning-based dialogue service, the method comprising:

• an machine learning-based dialogue service implemented by distributed network of computers:
• configuring one or more training data sourcing parameters to source a corpora of raw machine learning training data from the one or more sources of machine learning training data;
• obtaining, from the one or more sources of machine learning training data, the corpora of raw machine learning training data based on the one or more training data sourcing parameters;
• calculating, using the one or more hardware computing servers, one or more efficacy metrics of the corpora of raw machine learning training data;
• and
• identifying whether to train at least one machine learning classifier of the machine learning-based dialogue system based on the one or more efficacy metrics of the corpora of raw machine learning training data.