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Found 13 papers, 0 papers with code
Without Further Ado: Direct and Simultaneous Speech Translation by AppTek in 2021
This paper describes the offline and simultaneous speech translation systems developed at AppTek for IWSLT 2021.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Automatic Video Dubbing at AppTek
The revoicing usually comes with a changed script, mostly in a different language, and the revoicing should reproduce the original emotions, coherent with the body language, and lip synchronized.
SubER - A Metric for Automatic Evaluation of Subtitle Quality
This paper addresses the problem of evaluating the quality of automatically generated subtitles, which includes not only the quality of the machine-transcribed or translated speech, but also the quality of line segmentation and subtitle timing.
Neural Speech Translation at AppTek
This work describes AppTek’s speech translation pipeline that includes strong state-of-the-art automatic speech recognition (ASR) and neural machine translation (NMT) components.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
AppTek’s Submission to the IWSLT 2022 Isometric Spoken Language Translation Task
To participate in the Isometric Spoken Language Translation Task of the IWSLT 2022 evaluation, constrained condition, AppTek developed neural Transformer-based systems for English-to-German with various mechanisms of length control, ranging from source-side and target-side pseudo-tokens to encoding of remaining length in characters that replaces positional encoding.
AppTek's Submission to the IWSLT 2022 Isometric Spoken Language Translation Task
To participate in the Isometric Spoken Language Translation Task of the IWSLT 2022 evaluation, constrained condition, AppTek developed neural Transformer-based systems for English-to-German with various mechanisms of length control, ranging from source-side and target-side pseudo-tokens to encoding of remaining length in characters that replaces positional encoding.
SubER: A Metric for Automatic Evaluation of Subtitle Quality
This paper addresses the problem of evaluating the quality of automatically generated subtitles, which includes not only the quality of the machine-transcribed or translated speech, but also the quality of line segmentation and subtitle timing.
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University
AppTek and RWTH Aachen University team together to participate in the offline and simultaneous speech translation tracks of IWSLT 2020.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Neural Simultaneous Speech Translation Using Alignment-Based Chunking
In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency and quality.
Novel Applications of Factored Neural Machine Translation
In this work, we explore the usefulness of target factors in neural machine translation (NMT) beyond their original purpose of predicting word lemmas and their inflections, as proposed by Garc\`ia-Mart\`inez et al., 2016.
Customizing Neural Machine Translation for Subtitling
In this work, we customized a neural machine translation system for translation of subtitles in the domain of entertainment.
Neural and Statistical Methods for Leveraging Meta-information in Machine Translation
In this paper, we discuss different methods which use meta information and richer context that may accompany source language input to improve machine translation quality.
