Wenda Chen

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The Complex Independent Component Analysis (CICA) which extends Independent Component Analysis (ICA) to complex signals has found applications in various fields. The ICA with Reference (ICA-R) has recently gained popularity in semi-blind separation of signals when a priori information of the desired sources are available in the form of reference signals.(More)
Acquiring labeled speech for low-resource languages is a difficult task in the absence of native speakers of the language. One solution to this problem involves collecting speech transcriptions from crowd workers who are foreign or non-native speakers of a given target language. From these mismatched transcriptions, one can derive probabilistic phone(More)
It is extremely challenging to create training labels for building acoustic models of zero-resourced languages, in which conventional resources required for model training – lexicons, transcribed audio, or in extreme cases even orthographic system or a viable phone set design for the language – are unavailable. Here, language mismatched transcripts, in(More)
In this paper, we evaluate a set of linguistic rules for pronunciation variations in Singapore English. We collect and annotate a speech corpus for Singapore English and label it with IPA narrow transcriptions. Data driven pronunciation rules are derived using American English (Buckeye corpus) as a reference. We compare the data driven rules with linguistic(More)
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