System Description on Third Automatic Simultaneous Translation Workshop (2022)

Abstract: This paper shows my submission to the Third Automatic Simultaneous Translation Workshop at NAACL2022.The submission includes Chinese audio to English text task, Chinese text to English text tast, and English text to Spanish text task. For the two text-to-text tasks, I use the STACL model of PaddleNLP. As for the audio-to-text task, I first use DeepSpeech2 to translate the audio into text, then apply the STACL model to handle the text-to-text task. The submission results show that the used method can get low delay with a few training samples.

## introduction the submitted system consists of two parts. one is audio to text system, which can translate chinese audio into english text. the second part is the textto-text model, which can translate source text into the target language. in the text-to-text translation task, the used system is stacl model @xcite . all training data are processed by byte pair encoding @xcite . in addition, the strategies used by the model in training and inference are the same. for example, if the wait-k strategy in inference is 1, the wait-k in training is also 1. in the audio to text translation task, the deep-speech2 model @xcite is used as the preprocessing of the stacl model. the deep-speech2 model can translate audio (chinese) segments into text (chinese) segments and then input the segments into the stacl model to generate the target-language text. the submitted results show that the used stacl model has a low delay for text translation tasks. but the system can only generate the results with a high delay in the audio translation task. the rest of the paper is organized as follows. section 2 describes the training data used in the submitted system. section 3 describes the model, training strategy, and results. the conclusions are given in section 4. ## datasets in this section, i describe the datasets. ## conclusion this paper describes my submitted system at the third automatic simultaneous translation workshop. the system submitted has a low delay. i will conduct a further study about the speech recognition strategy in the future. kemal oflazer, acl 2002 by eugene charniak and dekang lin, and earlier acl and eacl formats written by several people, including john chen, henry s. thompson and donald walker. additional elements were taken from the formatting instructions of the international joint conference on artificial intelligence and the conference on computer vision and pattern recognition.