7 papers with code • 0 benchmarks • 0 datasets
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Most implemented papers
End-to-End Attention-based Large Vocabulary Speech Recognition
Many of the current state-of-the-art Large Vocabulary Continuous Speech Recognition Systems (LVCSR) are hybrids of neural networks and Hidden Markov Models (HMMs).
GIBBONFINDR: An R package for the detection and classification of acoustic signals
The recent improvements in recording technology, data storage and battery life have led to an increased interest in the use of passive acoustic monitoring for a variety of research questions.
Acoustic Model Adaptation from Raw Waveforms with SincNet
Raw waveform acoustic modelling has recently gained interest due to neural networks' ability to learn feature extraction, and the potential for finding better representations for a given scenario than hand-crafted features.
Multilingual Bottleneck Features for Improving ASR Performance of Code-Switched Speech in Under-Resourced Languages
In this work, we explore the benefits of using multilingual bottleneck features (mBNF) in acoustic modelling for the automatic speech recognition of code-switched (CS) speech in African languages.