Lecture 16 - Multilingual speech recognition
This lecture covered multilingual and low-resource speech recognition - how to develop speech recognition systems for a diversity of languages, most of which have very limited resources.
Introduction to the problem of multilingual speech technology - scale of the problem (many languages in the world), the problem of low levels of linguistic resources for most languages.
Multilingual and cross-lingual acoustic models - using hidden layers to learn multilingual representations
- Hat-swap - swapping in a language-specific output layer for a neural network used in a DNN/HMM hybrid
- Multilingual bottleneck features - training a bottleneck neural network with a shared multilingual bottleneck hidden units (with language specific output layers) for use as additional features in GMM or neural network systems
Morphs and words
Morphological rich languages and vocabulary size
Morfessor - unsupervised data-driven method for the segmentation of words into morpheme-like units
Morph-based language models
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