Abstract: Embodiments of the present disclosure relate to a speech translation method, an apparatus, an electronic device, and a medium. The method includes generating a speech representation corresponding to a source-language audio based on the audio. The method also includes obtaining prompt content related to a target language. In addition, the method also includes generating a target-language text corresponding to the audio based on the speech representation and the prompt content.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for speech translation, an electronic device, and a medium. The method includes obtaining an audio in a source language, where the audio includes a specific type of information. The method further includes obtaining prompt content related to a target language. In addition, the method further includes generating, based on the audio and the prompt content, a target-language text corresponding to the audio, where the target-language text includes a punctuation mark corresponding to the specific type of the information.

Abstract: The present application provides a model training method and apparatus, a speech-to-speech translation method and apparatus, and a medium. The method includes: obtaining a speech recognition sample and a real speech-to-speech translation sample; generating a pseudo-labeled speech-to-speech translation sample based on the speech recognition sample; and training a speech-to-speech translation model based on the pseudo-labeled speech-to-speech translation sample and the real speech-to-speech translation sample. Therefore, the model training precision can be improved.

Abstract: Embodiments of the disclosure relate to a method and apparatus for generating a speech translation model, an electronic device, and a medium. The method includes extracting, by a semantic feature extractor, a source semantic unit sequence of source language audio and a target semantic unit sequence of target language audio, wherein the source language audio corresponds to the target language audio. The method further includes adjusting a first decoder from a plurality of decoders based on the source semantic unit sequence and the target semantic unit sequence. The method further includes adjusting a second decoder of the plurality of decoders based on the source semantic unit sequence, the target semantic unit sequence, a source acoustic unit sequence of the source language audio, and a target acoustic unit sequence of the target language audio.

Abstract: The embodiment of the disclosure provides a voice data processing method, an apparatus, an electronic device and a storage medium. The method includes: obtaining voice data to be processed, and inputting the voice data to be processed into a pre-trained first voice processing model for feature extraction to obtain feature data to be processed corresponding to the voice data to be processed; inputting the feature data to be processed into a trained second voice processing model for reprocessing to obtain discretized feature data corresponding to the voice data to be processed.