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This paper proposes a first attempt to build an end-to-end speech-to-texttranslation system, which does not use source language transcription duringlearning or decoding. We propose a model for direct speech-to-text translation,which gives promising results on a small French-English synthetic corpus.Relaxing the need for source language transcription would drastically changethe data collection methodology in speech translation, especially inunder-resourced scenarios. For instance, in the former project DARPA TRANSTAC(speech translation from spoken Arabic dialects), a large effort was devoted tothe collection of speech transcripts (and a prerequisite to obtain transcriptswas often a detailed transcription guide for languages with little standardizedspelling). Now, if end-to-end approaches for speech-to-text translation aresuccessful, one might consider collecting data by asking bilingual speakers todirectly utter speech in the source language from target language textutterances. Such an approach has the advantage to be applicable to anyunwritten (source) language.

Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation