A wearable Braille‐to‐speech translation system is of great importance for providing auditory feedback in assisting blind people and people with speech impairment. However, previous reported Braille‐to‐speech translation systems still need to be improved in terms of comfortability or integration. Here, a Braille‐to‐speech translation system that uses dual‐functional electrostatic transducers which are made of fabric‐based materials and can be integrated into textiles is reported. Based on electrostatic induction, the electrostatic transducer can either serve as a tactile sensor or a loudspeaker with the same design. The proposed electrostatic transducers have excellent output performances, mechanical robustness, and working stability. By combining the devices with machine learning algorithms, it is possible to translate the Braille alphabet and 40 commonly used words (extensible) into speech with an accuracy of 99.09% and 97.08%, respectively. This work demonstrates a new approach for further developments of advanced assistive technology toward improving the lives of disabled people. This study introduces a new type of Braille‐to‐speech translation system that employs dual‐functional electrostatic transducers constructed from fabric‐based materials. Assisted by a machine learning algorithm, it is possible to translate the Braille alphabet and 40 commonly used words (extensible) into speech with an accuracy of 99.09% and 97.08%, respectively.