Abstract: The present disclosure discloses a method and device for speech recognition and decoding, pertaining to the field of speech processing. The method comprises: receiving speech information, and extracting an acoustic feature; computing information of the acoustic feature according to a connection sequential classification model; when a frame in the acoustic feature information is a non-blank model frame, performing linguistic information searching using a weighted finite state transducer adapting acoustic modeling information and storing historical data, or otherwise, discarding the frame. By establishing the connection sequential classification model, the acoustic modeling is more accurate. By using the weighted finite state transducer, model representation is more efficient, and nearly 50% of computation and memory resource consumption is reduced. By using a phoneme synchronization method during decoding, amount and times of computations are effectively reduced for model searching.