BUT Opensat 2019 Speech Recognition System
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Summary
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.
- Type
- preprint
- Published
- 2020-01-30
- Cited by
- 4
- References
- 19
- Access
- Open access
- OpenAlex
- https://openalex.org/W3004331963
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:210966312
Keywords
Computer science, Speech recognition, Domain (mathematical analysis), Process (computing), Noise (video)
References
- Attention-Based Models for Speech Recognition
- The Kaldi Speech Recognition Toolkit
- The language-independent bottleneck features
- Multilingual training of deep neural networks
- A pitch extraction algorithm tuned for automatic speech recognition
- Sequence-discriminative training of deep neural networks
- Reverberation robust acoustic modeling using i-vectors with time delay neural networks
- Enhancing low resource keyword spotting with automatically retrieved web documents
- Purely Sequence-Trained Neural Networks for ASR Based on Lattice-Free MMI
- Adapting multilingual neural network hierarchy to a new language
- Hybrid CTC/Attention Architecture for End-to-End Speech Recognition
- Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks
- BUT OpenSAT 2017 Speech Recognition System
- Optimizing Multilingual Knowledge Transfer for Time-Delay Neural Networks with Low-Rank Factorization
- Convolutional Self-Attention Networks
- ESPnet: End-to-End Speech Processing Toolkit
- 2016 BUT Babel System: Multilingual BLSTM Acoustic Model with i-Vector Based Adaptation
- Attention is All you Need
- Babel system : Multilingual BLSTM acoustic model with i-vector based adaptation
Cited by
- Speech Activity Detection Based on Multilingual Speech Recognition System
- Text Augmentation for Language Models in High Error Recognition Scenario
- A dual mode authentication technique of finger vein patterns extraction using synchronized speech signals
- Multitask Adaptation with Lattice-Free MMI for Multi-Genre Speech Recognition of Low Resource Languages
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