Recently, we have seen an increasing interest in the area of speech-to-text translation. This has led to astonishing improvements in this area. In contrast, the activities in the area of speech-to-speech translation is still limited, although it is essential to overcome the language barrier. We believe that one of the limiting factors is the availability of appropriate training data. We address this issue by creating LibriS2S, to our knowledge the first publicly available speech-to-speech training corpus between German and English. For this corpus, we used independently created audio for German and English leading to an unbiased pronunciation of the text in both languages. This allows the creation of a new text-to-speech and speech-to-speech translation model that directly learns to generate the speech signal based on the pronunciation of the source language. Using this created corpus, we propose Text-to-Speech models based on the example of the recently proposed FastSpeech 2 model that integrates source language information. We do this by adapting the model to take information such as the pitch, energy or transcript from the source speech as additional input.

Idiomatic expressions (or idioms) are phrases where the meaning of the phrase cannot be determined from the meaning of the individual words in the expression. Translating idioms between languages is therefore a challenging task. Transformer models based on contextual embeddings have advanced the state-of-the-art across many domains in the field of natural language processing. While research using transformers has advanced both idiom detection as well as idiom disambiguation, idiom translation has not seen a similar advancement. In this work, we investigate two approaches to fine-tuning a pretrained Text-to-Text Transfer Transformer (T5) model to perform idiom translation from English to German. The first approach directly translates English idiom-containing sentences to German, while the second is underpinned by idiom paraphrasing, firstly paraphrasing English idiomatic expressions to their simplified English versions before translating them to German. Results of our evaluation show that each of the approaches is able to generate adequate translations.