Genetics 发表于 2025-3-28 15:39:02
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G. Stellact representation of a speaker utterance extracted from a low dimensional total variability subspace. Although current speaker recognition systems achieve very good results in clean training and test conditions, the performance degrades considerably in noisy environments. The compensation of the no彻底明白 发表于 2025-3-29 01:50:01
F. Ladoentifica-tion of rhyme schemes in hip hop lyrics, which to the best of our knowledge, is the first such effort. Unlike previous approaches that use supervised or semi-supervised approaches for the task of rhyme scheme identification, our model does not assume any prior phonetic or labeling informati过份 发表于 2025-3-29 06:30:17
G. Parisised, each speech segment is described with a set of contextual features. These contextual features correspond to linguistic, phonetic and prosodic information that may affect the pronunciation of the segments. Gemination and vowel quantity (short vowel vs. long vowel) are two particular and importanNOVA 发表于 2025-3-29 07:18:54
http://reply.papertrans.cn/67/6649/664820/664820_45.png流出 发表于 2025-3-29 15:15:37
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B. Groh,S. Dietricha recorded in noisy and reverberant conditions is extremely limited, especially compared to the amount of data that can be . by adding noise to clean annotated speech. Thus, using both real and simulated data is important in order to improve robust speech recognition. Another promising method applieDysplasia 发表于 2025-3-30 03:29:20
S. Dietrichoften requires annotating in-domain data from scratch, as there is usually a lack of annotated resources for such scenarios. In this work, knowledge from a classifier learnt from a source annotated dataset is transferred to speed up the process of training a binary personal data identification class美食家 发表于 2025-3-30 07:58:45
M. L. Rosinberguage processing. In addition, most of the work in this domain addresses the English language because of the high availability of annotated training data compared to other languages. Therefore, we investigate methods for image captioning in German that transfer knowledge from English training data. W