A Two-Step Approach for Classifying Music Genre on the Strength of AHP Weighted Musical Features

Chen, Yu-Tso; Chen, Chi‐Hua; Wu, Szu Hui; Lo, Chi-Chun

doi:10.3390/math7010019

Cited by 47 publications

(35 citation statements)

References 21 publications

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“…With the technological development of hardware and software equipment, the ability and superiority of artificial intelligence have quickly penetrated into all areas of life, and of course, it has become the hottest vocabulary in the field of music technology [1]. We know that the promotion of music is actually based on technological changes.…”

Section: Introductionmentioning

confidence: 99%

Intonation Characteristics of Singing Based on Artificial Intelligence Technology and Its Application in Song-on-Demand Scoring System

Wei

2021

Mathematical Problems in Engineering

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With the continuous progress of my country’s cultural industry, how to apply artificial intelligence technology to song on demand has become an issue of concern. This research mainly discusses the research of singing intonation characteristics based on artificial intelligence technology and its application in song-on-demand scoring system. This paper uses the combination of ant colony algorithm and DTW algorithm to measure the similarity between speech signals with the average distortion distance, so as to expect accurate recognition results. The design of the song-on-demand scoring function module uses a combination of MVC mode and command mode based on artificial intelligence technology. The view component in the MVC mode is mainly used to display the content that the user needs to sing and realize the interaction with the user. The singer selects a song to start playing, and the scoring terminal device queries the music library server for song information according to the song number, then starts playing the song through the FTP file sharing service according to the audio file path in the song information, and at the same time displays the song on the display according to the timeline Show song and pitch information. The singer sings according to the screen prompts. The microphone collects the voice signal and transmits it to the scoring terminal. After the scoring algorithm is calculated, the result is fed back to the screen in real time. The singer can view his singing status in real time and make corresponding adjustments to obtain a higher score. After the singing, the scoring terminal will display the final result on the screen to inform the user and upload the singing record to the server for recording. In the tested on-demand retrieval engine, the average hit rate of the top 3 has reached more than 90% under various humming methods, basically maintaining the high hit rate characteristics of the original retrieval engine. The system designed in this research helps to effectively improve the singing level.

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Section: Introductionmentioning

confidence: 99%

Intonation Characteristics of Singing Based on Artificial Intelligence Technology and Its Application in Song-on-Demand Scoring System

Wei

2021

Mathematical Problems in Engineering

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“…The simulation results demonstrate that the proposed BP-QUATRE algorithm has better coverage rate than the other competing algorithms. In the future work, we will apply BL-QUATRE algorithm to classify music genre [41].…”

Section: Resultsmentioning

confidence: 99%

A bi-population QUasi-Affine TRansformation Evolution algorithm for global optimization and its application to dynamic deployment in wireless sensor networks

Liu

Pan

Nguyen

2019

J Wireless Com Network

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In this paper, we propose a new Bi-Population QUasi-Affine TRansformation Evolution (BP-QUATRE) algorithm for global optimization. The proposed BP-QUATRE algorithm divides the population into two subpopulations with sort strategy, and each subpopulation adopts a different mutation strategy to keep the balance between the fast convergence and population diversity. What is more, the proposed BP-QUATRE algorithm dynamically adjusts scale factor with a linear decrease strategy to make a good balance between exploration and exploitation capability. We compare the proposed algorithm with two QUATRE variants, PSO-IW, and DE algorithms on the CEC2013 test suite. The experimental results demonstrate that the proposed BP-QUATRE algorithm outperforms the competing algorithms. We also apply the proposed algorithm to dynamic deployment in wireless sensor networks. The simulation results show that the proposed BP-QUATRE algorithm has better coverage rate than the other competing algorithms.

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“…In the formula, x represents the input, W 1 represents the parameter matrix of the first linear transformation, b 1 represents the offset vector of the first linear transformation, W 2 represents the parameter matrix of the second linear transformation, and b 2 represents the offset vector of the second linear transformation [14].…”

Section: Andmentioning

confidence: 99%

Research on Uyghur-Chinese Neural Machine Translation Based on the Transformer at Multistrategy Segmentation Granularity

Qin

Hua

2021

Mobile Information Systems

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In recent years, machine translation based on neural networks has become the mainstream method in the field of machine translation, but there are still challenges of insufficient parallel corpus and sparse data in the field of low resource translation. Existing machine translation models are usually trained on word-granularity segmentation datasets. However, different segmentation granularities contain different grammatical and semantic features and information. Only considering word granularity will restrict the efficient training of neural machine translation systems. Aiming at the problem of data sparseness caused by the lack of Uyghur-Chinese parallel corpus and complex Uyghur morphology, this paper proposes a multistrategy segmentation granular training method for syllables, marked syllable, words, and syllable word fusion and targets traditional recurrent neural networks and convolutional neural networks; the disadvantage of the network is to build a Transformer Uyghur-Chinese Neural Machine Translation model based entirely on the multihead self-attention mechanism. In CCMT2019, dimension results on Uyghur-Chinese bilingual datasets show that the effect of multiple translation granularity training method is significantly better than the rest of granularity segmentation translation systems, while the Transformer model can obtain higher BLEU value than Uyghur-Chinese translation model based on Self-Attention-RNN.

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A Two-Step Approach for Classifying Music Genre on the Strength of AHP Weighted Musical Features

Cited by 47 publications

References 21 publications

Intonation Characteristics of Singing Based on Artificial Intelligence Technology and Its Application in Song-on-Demand Scoring System

Intonation Characteristics of Singing Based on Artificial Intelligence Technology and Its Application in Song-on-Demand Scoring System

A bi-population QUasi-Affine TRansformation Evolution algorithm for global optimization and its application to dynamic deployment in wireless sensor networks

Research on Uyghur-Chinese Neural Machine Translation Based on the Transformer at Multistrategy Segmentation Granularity

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