The type of voice model used in Computer Assisted Pronunciation Instruction is a crucial factor in the quality of practice and the amount of uptake by language learners. As an example, prior research indicates that second-language learners are more likely to succeed when they imitate a speaker with a voice similar to their own, a so-called “golden speaker”. This manuscript presents Golden Speaker Builder (GSB), a tool that allows learners to generate a personalized “golden-speaker” voice: one that mirrors their own voice but with a native accent. We describe the overall system design, including the web application with its user interface, and the underlying speech analysis/synthesis algorithms. Next, we present results from a series of listening tests, which show that GSB is capable of synthesizing such golden-speaker voices. Finally, we present results from a user study in a language-instruction setting, which show that practising with GSB leads to improved fluency and comprehensibility. We suggest reasons for why learners improved as they did and recommendations for the next iteration of the training.