Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Machines: Problem Solving II01:30

Machines: Problem Solving II

503
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
503
Machines: Problem Solving I01:22

Machines: Problem Solving I

530
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
530
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

248
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
248
Mechanical Efficiency of Real Machines01:14

Mechanical Efficiency of Real Machines

998
The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
However, in reality, no machine can be truly ideal, and all of them experience some...
998
Machines01:19

Machines

439
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
439
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

167
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
167

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same journal

Artificial intelligence applications in surgical education and training: a systematic review.

Frontiers in artificial intelligence·2026
Same journal

AI product liability under EU and Canadian laws.

Frontiers in artificial intelligence·2026
Same journal

Statistical limits and conditional complexity in real-world reinforcement learning: a tutorial survey.

Frontiers in artificial intelligence·2026
Same journal

Editorial: Advancing human wellbeing: environment-focused AI technologies.

Frontiers in artificial intelligence·2026
Same journal

Enhancing financial data collection and reporting in small businesses through IoT integration: an exploration of IFRS standard.

Frontiers in artificial intelligence·2026
Same journal

Automatic speech recognition for Telugu: a comparative analysis of Wav2Vec 2.0 model variants and hyperparameter tuning.

Frontiers in artificial intelligence·2026

Related Experiment Video

Updated: Nov 12, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

829

A Dynamic Representation Solution for Machine Learning-Aided Performance Technology.

Jason Palamara1, W Scott Deal2

  • 1Department of Music and Arts Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, United States.

Frontiers in Artificial Intelligence
|March 18, 2021
PubMed
Summary
This summary is machine-generated.

This study addresses confusion in music technology regarding dynamic representation. It introduces a novel system for context-dependent dynamics in machine learning-aided musical performance.

Keywords:
Ableton LiveMax for Livedynamic representationimprovisationmachine learning aided performancemusic and AImusic and machine learningmusic technology

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.5K

Related Experiment Videos

Last Updated: Nov 12, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

829
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.5K

Area of Science:

  • Music Technology
  • Machine Learning
  • Digital Signal Processing

Background:

  • Traditional musical dynamics (e.g., forte) lack precise decibel equivalents.
  • Digital music technologies struggle with context-dependent parameters due to discrete data representation.

Purpose of the Study:

  • To identify root causes of confusion in dynamic representation within music technology.
  • To introduce a system for context-dependent dynamics in machine learning-aided performance.
  • To enable more nuanced and context-aware musical expression in digital environments.

Main Methods:

  • Development of a system employing an adaptive process to interpret audio events.
  • Establishment of a novel definition for context-dependent dynamics tailored for music technologies.
  • Implementation of a generative program utilizing context-dependent dynamics and a Markov model for improvisational music generation.

Main Results:

  • The proposed system provides a solution for implementing context-dependent dynamics in digital music.
  • Musicians, composers, and producers can overcome challenges in applying dynamics to technology.
  • A generative program demonstrates the practical application of the system in novel music creation.

Conclusions:

  • The developed system effectively addresses the challenge of context-dependent dynamics in music technology.
  • This work facilitates more intuitive and expressive use of dynamics in machine learning-aided musical performances and compositions.
  • The findings pave the way for future advancements in intelligent music systems.