Shang-wen Li

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Gabor features have been proposed for extracting spectro-temporal modulation information from speech signals, and have been shown to yield large improvements in recognition accuracy. We use a flexible Tandem system framework that integrates multi-stream information including Gabor, MFCC, and pitch features in various ways, by modeling either or both of the(More)
We propose a method to enhance multi-stream Gabor and MFCC features using data-driven hierarchical phoneme clusters to yield more discriminating posteriors. We take into account different hierarchy structures, and in addition perform mean and variance normalization. A relative improvement of 11.5% over the conventional MFCC Tandem system was achieved in(More)
The increasing popularity of Massive Open Online Courses (MOOCs) has resulted in huge number of courses available over the Internet. Typically, a learner can type a search query into the look-up window of a MOOC platform and receive a set of course suggestions. But it is difficult for the learner to select lectures out of those suggested courses and learn(More)
We propose an improved Tandem system for tonal language speech recognition. Three different types of features, cepstral, spectro-temporal and pitch features, are integrated for modeling tone and phoneme variation simultaneously. Tonal phonemes (or tonemes) are used for MLP posterior estimation, and tonal acoustic units for HMM recognition. In our(More)
Gabor features have been proposed for extracting spectro-temporal modulation information, and yielding significant improvements in recognition performance. In this paper, we propose the integration of Gabor posteriors with MFCC posteriors, yielding a relative improvement of 14.3% over an MFCC Tandem system. We analyze for different types of acoustic units(More)
The sheer size of the student body for MOOC and the diversity of their learning styles and backgrounds demand that we develop alternatives to the one-size-fits-all pedagogy used in residential education. An important aspect of this endeavor is the segmentation of the video material, since it forms the omnipresent and central part of every course, and(More)
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