Task: Question Answering
Input (English): These features are typically obtained by training a deep neural network jointly on several languages for which labelled data is available. The bottom layers of the network are normally shared across all training languages. The network then splits into separate parts for each of the languages, or has a single shared output. The final output layer has phone labels or HMM states as targets. The final shared layer often has a lower dimensionality than the input layer, and is therefore referred to as a `bottleneck'. 
 Question: What are bottleneck features?
Output (English): Bulgarian, Czech, French, German, Korean, Polish, Portuguese, Russian, Thai, Vietnamese South African English These features are typically obtained by training a deep neural network jointly on several languages for which labelled data is available. The final shared layer often has a lower dimensionality than the input layer, and is therefore referred to as a `bottleneck'.