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Disambiguation of "Hung, Jeih-Weih"

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New approaches for domain transformation and parameter combination for improved accuracy in parallel model combination (PMC) techniques.

, , and . IEEE Trans. Speech Audio Process., 9 (8): 842-855 (2001)

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Yousef Jeihouni

Markus Weih

Frank Weih

Alexander Weih

Sandra Weih

 

Other publications of authors with the same name

Optimization of Temporal Filters in the Modulation Frequency Domain via Constrained Linear Discriminant Analysis (C-LDA) for Constructing Robust Features in Speech Recognition.. ICASSP (4), page 805-808. IEEE, (2007)Cepstral Statistics Compensation Using Online Pseudo Stereo Codebooks for Robust Speech Recognition in Additive Noise Environments.. ICASSP (1), page 513-516. IEEE, (2006)Enhancing the Magnitude Spectrum of Speech Features for Robust Speech Recognition., , and . EURASIP J. Adv. Signal Process., (2012)Robust Speech Recognition via Enhancing the Complex-Valued Acoustic Spectrum in Modulation Domain., , and . IEEE ACM Trans. Audio Speech Lang. Process., 24 (2): 236-251 (2016)Leveraging gain normalization for sub-band temporal features in noise-robust speech recognition., and . FSKD, page 1409-1412. IEEE, (2012)ConSep: a Noise- and Reverberation-Robust Speech Separation Framework by Magnitude Conditioning., , and . CoRR, (2024)Time-Reversal Enhancement Network With Cross-Domain Information for Noise-Robust Speech Recognition., , , and . IEEE Multim., 29 (1): 114-124 (2022)Subband Feature Statistics Normalization Techniques Based on a Discrete Wavelet Transform for Robust Speech Recognition., and . IEEE Signal Process. Lett., 16 (9): 806-809 (2009)強健性語音辨識中基於小波轉換之分頻統計補償技術的研究 (A Study of Sub-band Feature Statistics Compensation Techniques Based on a Discrete Wavelet Transform for Robust Speech Recognition) In Chinese., , and . ROCLING, Association for Computational Linguistics and Chinese Language Processing (ACLCLP), Taiwan, (2009)Employing low-pass filtered temporal speech features for the training of ideal ratio mask in speech enhancement., , and . ROCLING, page 236-242. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), (2021)