Search Results for author:
Found 18 papers, 1 papers with code
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning
{\%} Combining these techniques, we are able to provide an adapted speech translation system for several European languages.
Using multi-task learning to improve the performance of acoustic-to-word and conventional hybrid models
Acoustic-to-word (A2W) models that allow direct mapping from acoustic signals to word sequences are an appealing approach to end-to-end automatic speech recognition due to their simplicity.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Learning Shared Encoding Representation for End-to-End Speech Recognition Models
In this work, we learn a shared encoding representation for a multi-task neural network model optimized with connectionist temporal classification (CTC) and conventional framewise cross-entropy training criteria.
Very Deep Self-Attention Networks for End-to-End Speech Recognition
Recently, end-to-end sequence-to-sequence models for speech recognition have gained significant interest in the research community.
Improving sequence-to-sequence speech recognition training with on-the-fly data augmentation
Sequence-to-Sequence (S2S) models recently started to show state-of-the-art performance for automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Toward Cross-Domain Speech Recognition with End-to-End Models
We show that for the hybrid models, supplying additional training data from other domains with mismatched acoustic conditions does not increase the performance on specific domains.
High Performance Sequence-to-Sequence Model for Streaming Speech Recognition
However, when it comes to performing run-on recognition on an input stream of audio data while producing recognition results in real-time and with low word-based latency, these models face several challenges.
Removing European Language Barriers with Innovative Machine Translation Technology
This paper presents our progress towards deploying a versatile communication platform in the task of highly multilingual live speech translation for conferences and remote meetings live subtitling.
ELITR Non-Native Speech Translation at IWSLT 2020
This paper is an ELITR system submission for the non-native speech translation task at IWSLT 2020.
Super-Human Performance in Online Low-latency Recognition of Conversational Speech
Achieving super-human performance in recognizing human speech has been a goal for several decades, as researchers have worked on increasingly challenging tasks.
ELITR Multilingual Live Subtitling: Demo and Strategy
This paper presents an automatic speech translation system aimed at live subtitling of conference presentations.
ELITR: European Live Translator
ELITR (European Live Translator) project aims to create a speech translation system for simultaneous subtitling of conferences and online meetings targetting up to 43 languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
The IWSLT 2019 KIT Speech Translation System
This paper describes KIT’s submission to the IWSLT 2019 Speech Translation task on two sub-tasks corresponding to two different datasets.
KIT’s IWSLT 2018 SLT Translation System
The baseline system is a cascade of an ASR system, a system to segment the ASR output and a neural machine translation system.
The 2016 KIT IWSLT Speech-to-Text Systems for English and German
For the English TED task, our best combination system has a WER of 7. 8% on the development set while our other combinations gained 21. 8% and 28. 7% WERs for the English and German MSLT tasks.
The 2017 KIT IWSLT Speech-to-Text Systems for English and German
For the English lecture task, our best combination system has a WER of 8. 3% on the tst2015 development set while our other combinations gained 25. 7% WER for German lecture tasks.
Multi-stage Large Language Model Correction for Speech Recognition
In this paper, we investigate the usage of large language models (LLMs) to improve the performance of competitive speech recognition systems.
