CTC-based Non-autoregressive Textless Speech-to-Speech Translation
Direct speech-to-speech translation (S2ST) has achieved impressive translation quality, but it often faces the challenge of slow decoding due to the considerable length of speech sequences. Recently, some research has turned to non-autoregressive (NAR) models to expedite decoding, yet the translation quality typically lags behind autoregressive (AR) models significantly. In this paper, we investigate the performance of CTC-based NAR models in S2ST, as these models have shown impressive results in machine translation. Experimental results demonstrate that by combining pretraining, knowledge distillation, and advanced NAR training techniques such as glancing training and non-monotonic latent alignments, CTC-based NAR models achieve translation quality comparable to the AR model, while preserving up to 26.81$\times$ decoding speedup.
Code (1)
Tasks
Knowledge DistillationMachine TranslationSpeech-to-Speech TranslationTranslationSimilar Papers 제목 키워드 기반
Textless Speech-to-Speech Translation on Real Data
We present a textless speech-to-speech translation (S2ST) system that can translate speech from one language into another language and can be built without the need of any text data. Different from existing work in the l…
Speech-to-Speech TranslationTranslationTextless Speech-to-Speech Translation With Limited Parallel Data
Existing speech-to-speech translation (S2ST) models fall into two camps: they either leverage text as an intermediate step or require hundreds of hours of parallel speech data. Both approaches are incompatible with textl…
Automatic Speech RecognitionDenoisingLanguage ModellingMachine Translation+4TranSpeech: Speech-to-Speech Translation With Bilateral Perturbation
Direct speech-to-speech translation (S2ST) with discrete units leverages recent progress in speech representation learning. Specifically, a sequence of discrete representations derived in a self-supervised manner are pre…
Representation LearningRhythmSpeech Representation LearningSpeech Synthesis+2Textless Direct Speech-to-Speech Translation with Discrete Speech Representation
Research on speech-to-speech translation (S2ST) has progressed rapidly in recent years. Many end-to-end systems have been proposed and show advantages over conventional cascade systems, which are often composed of recogn…
Speech-to-Speech TranslationTranslationAnalyzing Speech Unit Selection for Textless Speech-to-Speech Translation
Recent advancements in textless speech-to-speech translation systems have been driven by the adoption of self-supervised learning techniques. Although most state-of-the-art systems adopt a similar architecture to transfo…
Automatic Speech RecognitionEmotion Recognitionfeature selectionResynthesis+7