A fragment-decoding plus missing-data imputation ASR system evaluated on the 2nd CHiME Challenge
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[1] Björn W. Schuller,et al. Noise robust ASR in reverberated multisource environments applying convolutive NMF and Long Short-Term Memory , 2013, Comput. Speech Lang..
[2] Ning Ma,et al. A hearing-inspired approach for distant-microphone speech recognition in the presence of multiple sources , 2013, Comput. Speech Lang..
[3] Jon Barker,et al. The second ‘chime’ speech separation and recognition challenge: Datasets, tasks and baselines , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[4] James Glass,et al. Research Developments and Directions in Speech Recognition and Understanding, Part 1 , 2009 .
[5] Brian R Glasberg,et al. Derivation of auditory filter shapes from notched-noise data , 1990, Hearing Research.
[6] John McDonough,et al. Distant Speech Recognition , 2009 .
[7] James R. Glass,et al. Developments and directions in speech recognition and understanding, Part 1 [DSP Education] , 2009, IEEE Signal Processing Magazine.
[8] Ning Ma,et al. The PASCAL CHiME speech separation and recognition challenge , 2013, Comput. Speech Lang..
[9] Israel Cohen,et al. Noise spectrum estimation in adverse environments: improved minima controlled recursive averaging , 2003, IEEE Trans. Speech Audio Process..
[10] Jean Paul Haton,et al. On noise masking for automatic missing data speech recognition: A survey and discussion , 2007, Comput. Speech Lang..
[11] Rainer Martin,et al. Noise power spectral density estimation based on optimal smoothing and minimum statistics , 2001, IEEE Trans. Speech Audio Process..
[12] Masakiyo Fujimoto,et al. Speech recognition in living rooms: Integrated speech enhancement and recognition system based on spatial, spectral and temporal modeling of sounds , 2013, Comput. Speech Lang..
[13] Richard M. Stern,et al. Reconstruction of missing features for robust speech recognition , 2004, Speech Commun..
[14] P. Renevey,et al. Detection of Reliable Features for Speech Recognition in Noisy Condi-tions Using a Statistical Criterion , 2001 .
[15] CookeMartin,et al. Robust automatic speech recognition with missing and unreliable acoustic data , 2001 .
[16] Ning Ma,et al. Coupling identification and reconstruction of missing features for noise-robust automatic speech recognition , 2012, INTERSPEECH.