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While vocal tract resonances (VTRs, or formants that are defined as such resonances) are known to play a critical role in human speech perception and in computer speech processing, there has been a lack of standard databases needed for the quantitative evaluation of automatic VTR extraction techniques. We report in this paper on our recent effort to create(More)
This paper investigates data augmentation for deep neural network acoustic modeling based on label-preserving transformations to deal with data sparsity. Two data augmentation approaches, vocal tract length perturbation (VTLP) and stochastic feature mapping (SFM), are investigated for both deep neural networks (DNNs) and convolutional neural networks(More)
In this paper we describe the data collection for the TBALL project (Technology Based Assessment of Language and Literacy) and report the results of our efforts. We focus on aspects of our corpus that distinguish it from currently available corpora. The speakers are children (grades K-4), largely non-native speakers of English, and from diverse(More)
Automatic speech recognition is a core component of many applications , including keyword search. In this paper we describe experiments on acoustic modeling, language modeling, and decoding for keyword search on a Cantonese conversational telephony corpus collected as part of the IARPA Babel program. We show that acoustic modeling techniques such as the(More)
In this paper, an MLLR-like adaptation approach is proposed whereby the transformation of the means is performed deter-ministically based on linearization of VTLN. Biases and adaptation of the variances are estimated statistically by the EM algorithm. In the discrete frequency domain, we show that under certain approximations, frequency warping with(More)
This paper presents an enhanced stochastic mapping technique in the discriminative feature (fMPE) space that exploits stereo data for noise robust LVCSR. Both MMSE and MAP estimates of the mapping are given and the performance of the two is investigated. Due to the iterative nature of the MAP estimate, we show that combining MMSE and MAP estimates is(More)
We present a system for keyword search on Cantonese conversational telephony audio, collected for the IARPA Babel program, that achieves good performance by combining postings lists produced by diverse speech recognition systems from three different research groups. We describe the keyword search task, the data on which the work was done, four different(More)