While NMT models are often trained with clean and well-structured text, spoken utterances contain multiple disfluencies and recognition errors which are not well modelled by NMT systems. Adaptation to ASR transcripts: ASR hypotheses exhibit very different features from those of the texts used to train neural machine translation (NMT) networks.Within the standard cascaded framework, researchers have encountered several difficulties, including: Moreover, industry applications usually display speech transcripts, alongside translations (as in our previous figure), making cascade approaches more realistic and practical. However, despite the architectural simplicity and minimal error propagation of such new systems, cascaded solutions are still widely used, mainly because of the data scarceness problem shown by direct approaches since most language pairs lack of parallel resources (speech signal/text translations). Recent systems perform speech translation following a direct approach where a single network is in charge to translate the input speech signal into target-language text. The figure below illustrates our ST pipeline. Let’s focus on the set up of live translating a French speech into English, to make it accessible to a wider audience. Given the French speech signal, the system first produces ASR transcriptions which are then segmented, corrected and formatted as French captions and translated into English. SpeechTranslator: Live speech translation system. simultaneously runs machine translation (MT) powered by our best quality translation models towards European Union languages (speech translation/subtitling),Īll of this with the lowest latency and in a dedicated and user-friendly interface. The task closely resembles simultaneous interpreting, which performs real-time multilingual translations. The next figure shows a screenshot of our live ST system interface where captions (left) as well as the corresponding English translations (right) are displayed.punctuates and segments the automatic speech recognition (ASR) output, making this automatically formatted and corrected transcription available to human reviewer and audience (speech transcription/captioning),.transcribes the original speech, partnering for this task with Vocapia Automatic Speech Recognition 2,.Starting with French or English as the source spoken language, Speech Translator : In the context of the upcoming French Presidency of European Union in January 2022, SYSTRAN has developed a tool called Speech Translator for real-time captioning and translation of single-speaker speeches or multi-speaker meetings. How to optimise the comfort and understanding experience of such large audience raises the issue of multilingualism that we discuss in this post. These events are transmitted in real time to a large audience, on all types of devices and anywhere in the world.Ĭaptioning and live translation 1 are seen as essential in order to ensure that these events reach a growing international audience. An increasing number of live events such as conferences, meetings, lectures, debates, radio and TV shows, etc. are nowadays being live streamed on video channels and social networks.
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