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On the k-Closest Substring and k-Consensus Pattern Problems
TLDR
We extend the random sampling strategy in [14] and [13] to give a deterministic PTAS for the k-Closest Substring problem. Expand
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Online speaking rate estimation using recurrent neural networks
TLDR
We propose an online speaking rate estimation model based on recurrent neural networks based on a set of speech features that are known to correlate with speech rhythm. Expand
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Convex Weighting Criteria for Speaking Rate Estimation
TLDR
Speaking rate estimation directly from the speech waveform is a long-standing problem in speech signal processing. Expand
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Acoustic and perceptual speech characteristics of native Mandarin speakers with Parkinson's disease.
This study examines acoustic features of speech production in speakers of Mandarin with Parkinson's disease (PD) and relates them to intelligibility outcomes. Data from 11 participants with PD and 7Expand
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Models for objective evaluation of dysarthric speech from data annotated by multiple listeners
TLDR
We propose a new algorithm to solve the multi-annotator problem for regression-based objective evaluation of dysarthric speech and show that our method outperforms other similar approaches. Expand
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Improving voice quality of HMM-based speech synthesis using voice conversion method
TLDR
We propose to use voice conversion method to transform synthetic speech toward the original so as to improve its quality. Expand
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Faster and more accurate global protein function assignment from protein interaction networks using the MFGO algorithm
On four proteins interaction datasets, including Vazquez dataset, YP dataset, DIP‐core dataset, and SPK dataset, MFGO was tested and compared with the popular MR (majority rule) and GOM methods.Expand
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Accent Identification by Combining Deep Neural Networks and Recurrent Neural Networks Trained on Long and Short Term Features
TLDR
A combination of long-term and short-term training is proposed in this paper. Expand
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Articulation Entropy: An Unsupervised Measure of Articulatory Precision
TLDR
We propose a new measure we call "articulation entropy" that serves as a proxy for the number of distinct phonemes a person produces when he or she speaks. Expand
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Simulating Dysarthric Speech for Training Data Augmentation in Clinical Speech Applications
TLDR
We propose a method for simulating training data for clinical speech applications by transforming healthy speech to dysarthric speech using adversarial training. Expand
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