Semi-supervised learning with semantic knowledge extraction for improved speech recognition in air traffic control
A Srinivasamurthy, P Motlicek… - … of Interspeech 2017, 2017 - infoscience.epfl.ch
Abstract Automatic Speech Recognition (ASR) can introduce higher levels of automation
into Air Traffic Control (ATC), where spoken language is still the predominant form of …
into Air Traffic Control (ATC), where spoken language is still the predominant form of …
Towards unsupervised learning of speech features in the wild
Recent work on unsupervised contrastive learning of speech representation has shown
promising results, but so far has mostly been applied to clean, curated speech datasets. Can …
promising results, but so far has mostly been applied to clean, curated speech datasets. Can …
Semi-supervised adaptation of assistant based speech recognition models for different approach areas
M Kleinert, H Helmke, G Siol, H Ehr… - 2018 IEEE/AIAA 37th …, 2018 - ieeexplore.ieee.org
Air Navigation Service Providers (ANSPs) replace paper flight strips through different digital
solutions. The instructed commands from an air traffic controller (ATCos) are then available …
solutions. The instructed commands from an air traffic controller (ATCos) are then available …
Semi-supervised acoustic model training for speech with code-switching
In the FAME! project, we aim to develop an automatic speech recognition (ASR) system for
Frisian-Dutch code-switching (CS) speech extracted from the archives of a local broadcaster …
Frisian-Dutch code-switching (CS) speech extracted from the archives of a local broadcaster …
Semi-supervised ensemble DNN acoustic model training
It is very important to exploit abundant unlabeled speech for improving the acoustic model
training in automatic speech recognition (ASR). Semi-supervised training methods …
training in automatic speech recognition (ASR). Semi-supervised training methods …
Semi-supervised model training for unbounded conversational speech recognition
For conversational large-vocabulary continuous speech recognition (LVCSR) tasks, up to
about two thousand hours of audio is commonly used to train state of the art models …
about two thousand hours of audio is commonly used to train state of the art models …
[HTML][HTML] Acoustic model bootstrapping using semi-supervised learning
L Chen - 2019 - amazon.science
This work aims at bootstrapping the acoustic model training with small amount of the human
annotated speech data and large amount of the unlabelled speech data for automatic …
annotated speech data and large amount of the unlabelled speech data for automatic …
[HTML][HTML] End-to-end automated speech recognition using a character based small scale transformer architecture
This study explores the feasibility of constructing a small-scale speech recognition system
capable of competing with larger, modern automated speech recognition (ASR) systems in …
capable of competing with larger, modern automated speech recognition (ASR) systems in …
In-vehicle voice interface with improved utterance classification accuracy using off-the-shelf cloud speech recognizer
T Homma, Y Obuchi, K Shima, R Ikeshita… - … on Information and …, 2018 - search.ieice.org
For voice-enabled car navigation systems that use a multi-purpose cloud speech recognition
service (cloud ASR), utterance classification that is robust against speech recognition errors …
service (cloud ASR), utterance classification that is robust against speech recognition errors …
A progress report of the Taiwan Mandarin radio speech corpus project
The Taiwan Mandarin Radio Speech Corpus contains 300 (and growing) hours of high-
quality recordings selected from Taiwan's National Education Radio (NER) archive. The …
quality recordings selected from Taiwan's National Education Radio (NER) archive. The …