非負矩陣分解法於語音調變頻譜強化之研究(A study of enhancing the modulation spectrum of speech signals via nonnegative matrix factorization)[In Chinese]
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Speech EnhancementSimilar Papers 제목 키워드 기반
Importance of Different Temporal Modulations of Speech: A Tale of Two Perspectives
2022-03-31
· Samik Sadhu, Hynek Hermansky
How important are different temporal speech modulations for speech recognition? We answer this question from two complementary perspectives. Firstly, we quantify the amount of phonetic \textit{information} in the modulat…
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2013-10-01 · ROCLINGIJCLCLP 2013 10
· Hao-teng Fan, Yi-zhang Cai, Jeih-weih Hung
Robust Speech Recognitionspeech-recognitionSpeech Recognition
調變頻譜分解之改良於強健性語音辨識(Several Refinements of Modulation Spectrum Factorization for Robust Speech Recognition) [In Chinese]
2015-10-01 · ROCLINGIJCLCLP 2015 10
· Ting-Hao Chang, Hsiao-Tsung Hung, Kuan-Yu Chen, Hsin-Min Wang 외
Robust Speech Recognitionspeech-recognitionSpeech Recognition
Feature Extraction, Modulation and Recognition of Mixed Signal Based on SVM
2022-07-28
· Rong Han, Zihuai Lin
This paper introduces likelihood-based and feature-based modulation recognition methods. In the feature-based modulation simulation part, instantaneous feature, cyclic spectrum, high-order cumulants, and wavelet transfor…
Multiple Narrow-band signals Direction Finding with TMLA by Nonuniform Period Modulation
2022-03-30
· Kebin Liu, Lening Zhang, Qingkui Zhan, Chong He
A new array signal reconstruction and signal-channel DOA estimation method based on TMLA by nonuniform period modulation are proposed. By using non-uniform period modulation, the harmonic component produced by different …