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Found 7 papers, 4 papers with code
Speech collage: code-switched audio generation by collaging monolingual corpora
Designing effective automatic speech recognition (ASR) systems for Code-Switching (CS) often depends on the availability of the transcribed CS resources.
Evaluating and reducing the distance between synthetic and real speech distributions
While modern Text-to-Speech (TTS) systems can produce natural-sounding speech, they remain unable to reproduce the full diversity found in natural speech data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Mask-combine Decoding and Classification Approach for Punctuation Prediction with real-time Inference Constraints
In this work, we unify several existing decoding strategies for punctuation prediction in one framework and introduce a novel strategy which utilises multiple predictions at each word across different windows.
Speaker Adaptive Training using Model Agnostic Meta-Learning
Speaker adaptive training (SAT) of neural network acoustic models learns models in a way that makes them more suitable for adaptation to test conditions.
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.
Lattice-based lightly-supervised acoustic model training
This text data can be used for lightly supervised training, in which text matching the audio is selected using an existing speech recognition model.
Learning to adapt: a meta-learning approach for speaker adaptation
The performance of automatic speech recognition systems can be improved by adapting an acoustic model to compensate for the mismatch between training and testing conditions, for example by adapting to unseen speakers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
