HOW DOES IT WORK?
Machine learning helps systems learn how to recognize voice, handwriting, text or other input data to build reliable models and predictions. Thanks to such solutions, it is then possible for instance, for our mobile phones to react to voice commands, or for chatboxes to solve most common customers’ problems in automated customer service.
But to be able to learn, they need to be trained properly.
Training data collection includes gathering such training materials (called training data, training data for AI, training data sets) for machine learning to search and analyse them. Importantly, depending on the AI systems and their purpose, training data sets might include text, handwriting, audio, voice or labels.
If it comes to training data collection, it’s crucial to collect, annotate and validate the training data properly and efficiently. The data sets always need to be validated – include no errors, duplications, or any other faulty records that could confuse “the student” being the AI system developed. Having collected millions of screens of handwriting and voice recordings, we are a trusted partner in collecting the highest-quality training data for AI.
TYPES OF TRAINING DATA
Training data format depends on the functions planned for the AI systems. Data sets might include text, voice, handwriting or annotation data.
TEXT
VOICE
HANDWRITING
ANNOTATION
Training data format depends on the functions planned for the AI systems. Data sets might include text, voice, handwriting or annotation data.
TRAINING DATA COLLECTION
STEP BY STEP
PROJECT REQUIREMENTS AND SET-UP
Depending on the project, this stage might include the review of corpora files in target languages, organization of supervisors, vendors and/or venues, recruitment of respondents.
DATA COLLECTION
Then, we move forward to collecting quality samples of text, voice recordings, handwriting samples or annotation tags and labels.
DATA VALIDATION
Last but not least, we might help you with proofreading and data validation to provide the best-quality data set for machine learning.