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Found 6 papers, 0 papers with code
Feature learning for efficient ASR-free keyword spotting in low-resource languages
We show that, using these features, the CNN-DTW keyword spotter performs almost as well as the DTW keyword spotter while outperforming a baseline CNN trained only on the keyword templates.
Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training
The automatic transcriptions from the best performing pass were used for language model augmentation.
Feature exploration for almost zero-resource ASR-free keyword spotting using a multilingual bottleneck extractor and correspondence autoencoders
We compare features for dynamic time warping (DTW) when used to bootstrap keyword spotting (KWS) in an almost zero-resource setting.
Automatic Speech Recognition for Humanitarian Applications in Somali
We present our first efforts in building an automatic speech recognition system for Somali, an under-resourced language, using 1. 57 hrs of annotated speech for acoustic model training.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
ASR-free CNN-DTW keyword spotting using multilingual bottleneck features for almost zero-resource languages
We consider multilingual bottleneck features (BNFs) for nearly zero-resource keyword spotting.
Fast ASR-free and almost zero-resource keyword spotting using DTW and CNNs for humanitarian monitoring
While the resulting CNN keyword spotter cannot match the performance of the DTW-based system, it substantially outperforms a CNN classifier trained only on the keywords, improving the area under the ROC curve from 0. 54 to 0. 64.
