BUT Opensat 2019 Speech Recognition System
This work addresses ASR challenges in resource-limited and high-noise environments, but it is incremental as it builds on existing methods.
The paper tackled speech recognition for low-resource languages and public safety communications, achieving superior performance through multilingual approaches and data augmentation for extreme conditions.
The paper describes the BUT Automatic Speech Recognition (ASR) systems submitted for OpenSAT evaluations under two domain categories such as low resourced languages and public safety communications. The first was challenging due to lack of training data, therefore various architectures and multilingual approaches were employed. The combination led to superior performance. The second domain was challenging due to recording in extreme conditions such as specific channel, speaker under stress and high levels of noise. Data augmentation process was inevitable to get reasonably good performance.