Conformer-1’s architecture

AssemblyAI has achieved state-of-the-art performance for speech recognition models with the release of Conformer-1, a new model utilizing the Conformer architecture, which integrates convolutional neural networks with transformer models. Conformer-1 achieves an average weighted edit rate (WER) across multiple domains and languages that is 43% lower than competitors when trained on up to 70 thousand hours of diverse audio data. This new model demonstrates high accuracy and robustness to real-world audio data, even in the presence of noise. Conformer-1 is currently available through AssemblyAI's API and can be tested via their Playground or by signing up for a free API token.