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» Temporal Feature Selection for Noisy Speech Recognition
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ICASSP
2011
IEEE
14 years 1 months ago
Forensically inspired approaches to automatic speaker recognition
This paper presents ongoing research leveraging forensic methods for automatic speaker recognition. Some of the methods forensic scientists employ include identifying speaker dist...
Kyu J. Han, Mohamed Kamal Omar, Jason W. Pelecanos...
NIPS
2001
14 years 11 months ago
Sequential Noise Compensation by Sequential Monte Carlo Method
We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...
K. Yao, S. Nakamura
MT
2002
297views more  MT 2002»
14 years 9 months ago
MARS: A Statistical Semantic Parsing and Generation-Based Multilingual Automatic tRanslation System
We present MARS (Multilingual Automatic tRanslation System), a research prototype speech-to-speech translation system. MARS is aimed at two-way conversational spoken language trans...
Yuqing Gao, Bowen Zhou, Zijian Diao, Jeffrey S. So...
TASLP
2011
14 years 4 months ago
Time-Frequency Cepstral Features and Heteroscedastic Linear Discriminant Analysis for Language Recognition
Abstract—The shifted delta cepstrum (SDC) is a widely used feature extraction for language recognition (LRE). With a high context width due to incorporation of multiple frames, S...
Weiqiang Zhang, Liang He, Yan Deng, Jia Liu, M. T....
ICPR
2002
IEEE
15 years 2 months ago
Feature Extraction Methods Applied to the Clustering of Electrocardiographic Signals. A Comparative Study
In this paper, a method to automatically extract the main information from a long-term electrocardiographic signal is presented. This method is based on techniques of pattern reco...
David Cuesta-Frau, Juan Carlos Pérez-Cortes...