scholarly journals A Study of Piano Timbre Teaching in the Context of Artificial Intelligence Interaction

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Cui Wei
Keyword(s):  
Artificial Intelligence ◽  
Undergraduate Students ◽  
Teaching Practice ◽  
Development Trend ◽  
Teaching Experiment ◽  
Experimental Results ◽  
Piano Teaching ◽  
Teaching Objectives ◽  
Depth Analysis ◽  
Software Modules

This paper provides an in-depth analysis and research on piano timbre teaching in the context of artificial intelligence interaction, a bold vision of piano teaching, proposes a feasible solution in terms of teaching modules in intelligent piano teaching for senior teachers, and proposes an implementation path for the integration of intelligent piano and piano teaching from the four main blocks of piano teaching. Based on the multiplicative harmonic model of monophonic signal, combined with the variability of timbre characteristics, an audio synthesis model with editable timbre is proposed, and the experimental results show that editing the timbre parameters in the model can realize timbre modification, and the synthesized timbre conforms to the piano timbre characteristics. Based on the timbre analysis and the timbre synthesis model, a piano timbre library generation system is designed. The detailed design of the software modules such as audio file reading and writing, audio information analysis, timbre parameter acquisition, timbre synthesis, and simulated performance is given. The system can generate piano timbre libraries of different qualities flexibly and meet the requirements of timbre realism. The teaching experiment designed for teaching practice from solo teaching, and the practice target is first-year undergraduate students in the university, and the practice period is six weeks, and finally, the feasibility of intelligent piano teaching application is analysed by combining the experimental results. Through the teaching objectives, teaching content, and teaching methods, teaching environment reflects intelligent piano teaching to make up for the limitations of traditional piano teaching. Analyse the development trend of intelligent piano teaching in the context of artificial intelligence interaction, and explore the value of intelligent piano teaching.

Reinforcement Learning for Cloud Computing Digital Library

2014 ◽  
Vol 571-572 ◽  
pp. 105-108
Author(s):  
Lin Xu
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Reinforcement Learning ◽  
Digital Library ◽  
Learning Algorithms ◽  
Experimental Results ◽  
Current Status ◽  
Self Learning ◽  
New Framework

This paper proposes a new framework of combining reinforcement learning with cloud computing digital library. Unified self-learning algorithms, which includes reinforcement learning, artificial intelligence and etc, have led to many essential advances. Given the current status of highly-available models, analysts urgently desire the deployment of write-ahead logging. In this paper we examine how DNS can be applied to the investigation of superblocks, and introduce the reinforcement learning to improve the quality of current cloud computing digital library. The experimental results show that the method works more efficiency.

scholarly journals Application of Sensors in Intelligent Clothing Design

2018 ◽  
Vol 14 (06) ◽  
pp. 4
Author(s):  
Shali Jiang ◽  
Qiong Ren
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Experimental Results ◽  
Machine Learning Method ◽  
Learning Method ◽  
Clothing Design ◽  
Artificial Intelligence Technology ◽  
Contact Sensor ◽  
Intelligent Clothing ◽  
Contact Sensors

<p class="0abstract"><span lang="EN-US">In order to study the application of sensors in intelligent clothing design, the artificially intelligent cutting-edge technology -machine learning method was proposed to combine a variety of signals of non-contact sensors in several different positions. Higher accuracy was achieved, while maintaining the comfort brought by a non-contact sensor. The experimental results showed that the proposed strategy focused on the combination of clothing design technology and artificial intelligence technology. As a result, without changing the sensor materials, it enhances the comfort and precision of clothing, eliminates the comfort reduced by sensor close to the skin, and transforms inaccurate measurement into accurate measurement. </span></p>

Retrieving Assembly Part Design Using Case-Based Reasoning and Genetic Algorithms

2005 ◽  
Author(s):  
Guanghsu A. Chang ◽  
Cheng-Chung Su ◽  
John W. Priest
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithms ◽  
Nearest Neighbor ◽  
Similarity Measures ◽  
Experimental Results ◽  
Case Based Reasoning ◽  
Feature Weight ◽  
Similar Part ◽  
Case Base ◽  
Case Based

Artificial intelligence (AI) approaches have been successfully applied to many fields. Among the numerous AI approaches, Case-Based Reasoning (CBR) is an approach that mainly focuses on the reuse of knowledge and experience. However, little work is done on applications of CBR to improve assembly part design. Similarity measures and the weight of different features are crucial in determining the accuracy of retrieving cases from the case base. To develop the weight of part features and retrieve a similar part design, the research proposes using Genetic Algorithms (GAs) to learn the optimum feature weight and employing nearest-neighbor technique to measure the similarity of assembly part design. Early experimental results indicate that the similar part design is effectively retrieved by these similarity measures.

scholarly journals Automatic Synthesis of Generalized Winning Strategies of Impartial Combinatorial Games Using SMT Solvers

2020 ◽  
Author(s):  
Kaisheng Wu ◽  
Liangda Fang ◽  
Liping Xiong ◽  
Zhao-Rong Lai ◽  
Yong Qiao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Game Theory ◽  
Experimental Results ◽  
Combinatorial Games ◽  
Logical Framework ◽  
Automatic Synthesis ◽  
Integer Arithmetic ◽  
Smt Solvers ◽  
Winning Strategies

Strategy representation and reasoning has recently received much attention in artificial intelligence. Impartial combinatorial games (ICGs) are a type of elementary and fundamental games in game theory. One of the challenging problems of ICGs is to construct winning strategies, particularly, generalized winning strategies for possibly infinitely many instances of ICGs. In this paper, we investigate synthesizing generalized winning strategies for ICGs. To this end, we first propose a logical framework to formalize ICGs based on the linear integer arithmetic fragment of numeric part of PDDL. We then propose an approach to generating the winning formula that exactly captures the states in which the player can force to win. Furthermore, we compute winning strategies for ICGs based on the winning formula. Experimental results on several games demonstrate the effectiveness of our approach.

scholarly journals Connotation Analysis and Paradigm Shift of Teaching Design under Artificial Intelligence Technology

2021 ◽  
Vol 16 (05) ◽  
pp. 73
Author(s):  
Jian Huang ◽  
Gang Shen ◽  
Xiping Ren
Keyword(s):  
Artificial Intelligence ◽  
Paradigm Shift ◽  
Learning Ability ◽  
Teaching Activities ◽  
Learning Efficiency ◽  
Teaching Objectives ◽  
Teaching Design ◽  
Teachers And Students ◽  
Artificial Intelligence Technology ◽  
Teaching Efficiency

The influence of artificial intelligence technology on teaching design is explored to improve teaching efficiency. First, artificial intelligence is introduced and its impacts on teaching design are analyzed. Second, the connotation of the paradigm of teaching design and the paradigm shift for teaching design are explored using the paradigm shift analysis framework. Finally, the changes in teaching design under artificial intelligence are analyzed, and the impacts of artificial intelligence on teaching activities are investigated. The results show that the application of artificial intelligence technology has led to different levels of change in the six elements of teaching design, including teaching objectives, service objects (teachers and students), teaching content, teaching media, teaching environment, and teaching evaluation. The connotation and paradigm shift of the teaching design are introduced from the four elements based on the artificial intelligence technology. It is found that artificial intelligence technology can enhance the learning ability and cognitive ability of students to a certain extent while improving the teaching efficiency and learning efficiency. The investigation proves that the teaching design based on artificial intelligence technology can be applied to teaching activities, thereby improving the learning efficiency of students and the teaching efficiency of teachers.

scholarly journals Breakdown Detection in Negotiation Dialogues (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13969-13970
Author(s):  
Atsuki Yamaguchi ◽  
Katsuhide Fujita
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Language Model ◽  
Experimental Results ◽  
Conflicts Of Interests ◽  
Early Stages ◽  
End To End ◽  
Gated Recurrent Unit

In human-human negotiation, reaching a rational agreement can be difficult, and unfortunately, the negotiations sometimes break down because of conflicts of interests. If artificial intelligence can play a role in assisting with human-human negotiation, it can assist in avoiding negotiation breakdown, leading to a rational agreement. Therefore, this study focuses on end-to-end tasks for predicting the outcome of a negotiation dialogue in natural language. Our task is modeled using a gated recurrent unit and a pre-trained language model: BERT as the baseline. Experimental results demonstrate that the proposed tasks are feasible on two negotiation dialogue datasets, and that signs of a breakdown can be detected in the early stages using the baselines even if the models are used in a partial dialogue history.

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