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In this work, we propose a novel method for vocabulary selection to automatically adapt automatic speech recognition systems to the diverse topics that occur in educational and scientific lectures. Utilizing materials that are available before the lecture begins, such as lecture slides, our proposed framework iteratively searches for related documents on(More)
In this work, we propose a novel method for vocabulary selection which enables simultaneous lecture translation systems to automatically adapt to the diverse topics that occur in educational and scientific lectures. Utilizing materials that are available before the lecture begins, such as lecture slides, our proposed framework iteratively searches for(More)
In this work, we investigate methods to automatically adapt our simultaneous lecture translation systems to the diverse topics that occur in educational lectures. Utilizing materials that are available before the lecture begins, such as lecture slides, our proposed framework iteratively searches for related documents on the World Wide Web and generates(More)
Adult-targeted automatic speech recognition (ASR) has made significant advancements in recent years and can produce speech-to-text output with very low word-error-rate, for multiple languages, and in various types of noisy environments, e.g. car noise, living-room, outdoor-noise, etc. But when it comes to child speech, little is available at the performance(More)
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