灰心丧气
发表于 2025-3-27 00:23:57
https://doi.org/10.1007/978-3-319-47217-1sic therapy in diabetes by using Beck Anxiety Method and Beck Depression Inventory methods with reliability of 0.67. The research methodology mainly focuses on the pre-evaluation stage, post-evaluation stages, and follow-up stages on diabetes patients. The reduced mean and covariance values evaluates the effectiveness of music therapy.
tenuous
发表于 2025-3-27 02:42:58
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incision
发表于 2025-3-27 06:52:52
Computer and Information Science 2021 - Fallw and why biases appear in MRS. A set of guidelines for handling biases is then proposed. Moreover, the specific case of non-superstar artists is analyzed from the point of view of datasets, considering its relevance for understanding biases.
蔑视
发表于 2025-3-27 11:19:33
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推迟
发表于 2025-3-27 15:53:03
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Circumscribe
发表于 2025-3-27 20:38:17
Music Composition with Deep Learning: A Review that are related to the hierarchy of musical language. Music generation has faced challenges by using algorithmic methods and recently is approaching them with deep learning models that are being used in other fields such as computer vision. In this chapter, we place into context the existing relat
歌剧等
发表于 2025-3-27 22:49:58
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使人入神
发表于 2025-3-28 04:50:16
Music Recommender Systems: A Review Centered on Biasesers interested in exploring new musical content do not always feel satisfied with the results obtained. Songs composed by some artists have very little chance of being recommended, and listeners in most cases repeatedly find the same songs. This chapter presents a review of the literature relating t
hankering
发表于 2025-3-28 07:46:11
Computational Approaches for Indian Classical Music: A Comprehensive Reviewtract helpful information needed to perform various musical tasks. Classical music in the Indian subcontinent, known as Indian classical music (ICM), has a long tradition and many followers. ICM has always been less researched, but it has changed in the past decade. Many researchers have started foc
格言
发表于 2025-3-28 14:12:21
A Study on Effectiveness of Deep Neural Networks for Speech Signal Enhancement in Comparison with Wispeech signal is highly susceptible to various noises. Many denoising methods include the removal of high-frequency components from the original signal, but this leads to the removal of parts of the original signal. Thus, the quality of the signal reduces which is highly undesirable. Our main object