In a recent paper entitled Optimizing the Design and Cost for Crowdsourced Conversational Utterances, Appen data scientist Phoebe Liu and her team worked to identify cost-effective crowdsourcing strategies for training dialogue systems such as chatbots. Because more industries are adopting chatbot technology for customer service and other key functions, a need has emerged for training these systems as quickly and …
When planning the development of a chatbot or virtual assistant, it’s important to begin the conversational design process with a clear data strategy in place. Conversational design requires more than just an understanding of the fundamentals of voice user interface design — you also need to understand how to solve some of the key challenges in data preparation. Working with the …
Appen is gearing up for some of the world’s leading industry events this summer. Our team will be exhibiting at conferences and trade shows around the globe, showing organizations how our services and solutions help develop high-quality training data for machine learning. Planning to attend one of these events? Contact us to set up a meeting with one of our …
For many organizations, the temptation to annotate data for machine learning (ML) projects in-house is hard to deny. These companies typically feel that using internal resources will help them save time and money by tapping employees who are already on their payroll. Additionally, if their project is highly confidential or of a sensitive nature, they might feel that using internal …
