Corpus Augmentation for Neural Machine Translation with Chinese-Japanese Parallel Corpora

Zhang, Jinyi; Matsumoto, Tadahiro

doi:10.3390/app9102036

Cited by 27 publications

(22 citation statements)

References 17 publications

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“…Taking into account the types of English songs used in this article, the lyrics of the songs include English and other different types of languages. In order to ensure the compatibility of the system with multiple languages, this article cuts the words of each character in English songs according to special characters, which guarantees the versatility and fluency of the word-slicing algorithm [32][33][34][35]. e word vector expresses the adaptive expression method of dynamic lyrics recognition and segmentation.…”

Section: Word Vector Pre-representation Of Lyrics Textmentioning

confidence: 99%

Multimodal Music Emotion Recognition Method Based on the Combination of Knowledge Distillation and Transfer Learning

Tong

2022

Scientific Programming

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The main difficulty of music emotion recognition is the lack of sufficient labeled data. Only the labeled data with unbalanced categories are used to train the emotion recognition model. Not only is accurate labeling of emotion categories costly and time-consuming, but it also requires extensive musical background for labelers At the same time, the emotion of music is often affected by many factors. Singing methods, music styles, arrangement methods, lyrics, and other factors will affect the expression of music emotions. This paper proposes a multimodal method based on the combination of knowledge distillation and music style transfer learning and verifies the effectiveness of the method on 20,000 songs. Experiments show that compared with traditional methods, such as single audio, single lyric, and single audio with multimodal lyric methods, the method proposed in this paper has significantly improved the accuracy of emotion recognition, and the generalization ability has been significantly improved.

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Section: Word Vector Pre-representation Of Lyrics Textmentioning

confidence: 99%

Multimodal Music Emotion Recognition Method Based on the Combination of Knowledge Distillation and Transfer Learning

Tong

2022

Scientific Programming

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“…However, it does not solve the problems of the single acquisition method of data resources in the existing marketing strategy, the acquisition of fewer resources, and the inability to achieve deep learning processing of data resources, and the setting and placement of advertisements based on data resources. For this reason, we propose a marketing strategy based on deep machine learning algorithms [24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

New Media Marketing Strategy Optimization in the Catering Industry Based on Deep Machine Learning Algorithms

Peng

2022

Journal of Mathematics

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With the in-depth development of new-generation network technologies such as the Internet, big data, and cloud intelligence, people can obtain massive amounts of information on mobile phones or mobile platforms. The era of unreachable big data has arrived, which raises questions for the development of corporate marketing. With the development of Internet technology, people use mobile terminals for longer and longer periods of time. New media has gradually become the mainstream of the media arena. It has distinctive features such as freedom to find audiences, diverse content forms, and timeliness of information release, which has changed the traditional. The marketing model has a profound impact on the development of the market. This article uses relevant theories, such as new media, marketing, and catering industry marketing strategies, studies the related concepts and characteristics of new media, clarifies the impact of the development of new media on the catering industry and audience groups, and studies the impact of the catering industry from multiple dimensions. Based on the development factors in the new media environment, combined with marketing theory, it puts forward suggestions for catering companies to use new media to carry out marketing planning in product innovation, improving information channels, creating network events and topics, and promoting innovation and health in the catering industry. And a marketing strategy is proposed based on deep machine learning algorithms; including a cloud server, the cloud server communicates with the e-commerce software platform and the input of physical sales is recorded. The adopted cloud server is connected with data collection, data processing, and communication module. The communication module is connected with a deep machine learning algorithm system; that is, deep machine learning algorithm system is connected with a sales platform in communication. The sales platform is connected with advertising settings and advertising, and the advertising is electrically connected with an algorithm of advertising delivery methods. Advertisement delivery method algorithm communication is connected to the cloud server. This article uses deep machine learning algorithms to process the data information to make the data information easy to view and clear. The advertisement delivery method algorithm calculates the best way of advertising and then calculates the advertisement to deliver.

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“…e application of deep learning theory can better solve these problems of statistical machine translation. Existing research methods mainly include two kinds: one uses deep learning technology to improve key modules and built the model to achieve direct source language to target language [23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Two-Way Neural Network Chinese-English Machine Translation Model Fused with Attention Mechanism

Liang

2022

Scientific Programming

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This study uses an end-to-end encoder-decoder structure to build a machine translation model, allowing the machine to automatically learn features and transform the corpus data into distributed representations. The word vector uses a neural network to achieve direct mapping. Research on constructing neural machine translation models for different neural network structures. Based on the translation model of the LSTM network, the gate valve mechanism reduces the gradient attenuation and improves the ability to process long-distance sequences. Based on the GRU network structure, the simplified processing is performed on the basis of it, which reduces the training complexity and achieves good performance. Aiming at the problem that some source language sequences of any length in the encoder are encoded into fixed-dimensional background vectors, the attention mechanism is introduced to dynamically adjust the degree of influence of the source language context on the target language sequence, and the translation model’s ability to deal with long-distance dependencies is improved. In order to better reflect the context information, this study further proposes a machine translation model based on two-way GRU and compares and analyzes multiple translation models to verify the effectiveness of the model’s performance improvement.

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Corpus Augmentation for Neural Machine Translation with Chinese-Japanese Parallel Corpora

Cited by 27 publications

References 17 publications

Multimodal Music Emotion Recognition Method Based on the Combination of Knowledge Distillation and Transfer Learning

Multimodal Music Emotion Recognition Method Based on the Combination of Knowledge Distillation and Transfer Learning

New Media Marketing Strategy Optimization in the Catering Industry Based on Deep Machine Learning Algorithms

Two-Way Neural Network Chinese-English Machine Translation Model Fused with Attention Mechanism

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