Researchers are continuously finding ways to improve speech recognition technology to better understand and process human speech across multiple languages and contexts. The challenge is developing models that accurately recognize speech from different languages and dialects. The recent introduction of OWSM v3.1, utilizing the E-Branchformer architecture, has shown significant advancements in this technology. This new architecture has proven to be faster and better in recognizing and interpreting speech nuances, such as dialects and accents. OWSM v3.1 also produces more accurate results than its predecessor. The model showcases up to 25% faster inference speed and demonstrates improvements in English-to-X translation across multiple languages. This research significantly contributes to enhancing speech recognition technology, setting a new standard for open-source speech recognition solutions. For more information, you can check out the Paper and Demo linked above.