Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Sound Intensity Level00:53

Sound Intensity Level

4.2K
Humans perceive sound by hearing. The human ear helps sound waves reach the brain, which then interprets the waves and creates the perception of hearing. The loudness of the environment in which a person is located determines whether they can distinguish between different sound sources.
The human ear can perceive an extensive range of sound intensity, necessitating the use of the logarithmic scale to define a physical quantity—the intensity level. It is a ratio of two intensities and...
4.2K
Force Classification01:22

Force Classification

1.2K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.2K
Korotkoff Sounds01:12

Korotkoff Sounds

3.4K
Korotkoff sounds are the specific sounds heard while measuring blood pressure using a sphygmomanometer, typically with a stethoscope or a Doppler device. They are named after Russian physician Nikolai Korotkov, who first described them in 1905. These sounds correspond to turbulent blood flow in the artery as the blood pressure cuff is gradually released after inflation.
During blood pressure assessment, inflating the cuff 30 millimeters of mercury above the patient's systolic blood pressure...
3.4K
Classification of Signals01:30

Classification of Signals

471
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
471
Data Collection by Observations01:08

Data Collection by Observations

12.0K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
12.0K
Sound Intensity00:58

Sound Intensity

4.0K
The loudness of a sound source is related to how energetically the source is vibrating, consequently making the molecules of the propagation medium vibrate. To measure the loudness of a source, the physical quantity of interest is the intensity. This is defined as the energy emitted per unit of time per unit of area perpendicular to the sound wave's propagation direction. Since the total energy is greater if the source vibrates for a longer duration and over a larger area, dividing the...
4.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Comparing point counts, passive acoustic monitoring, citizen science and machine learning for bird species monitoring in the Mount Kenya ecosystem.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2025
Same author

Self-Supervised Multi-Task Learning for the Detection and Classification of RHD-Induced Valvular Pathology.

Journal of imaging·2025
Same author

Barriers to global engagement for African researchers: A position paper from the Alliance for Medical Research in Africa (AMedRA).

Journal of global health·2024
Same author

A hybrid PSO-GWO-based phase shift design for a hybrid-RIS-aided heterogeneous network system.

Heliyon·2024
Same author

Low cost, LoRa based river water level data acquisition system.

HardwareX·2023
Same author

DSAIL-Porini: Annotated camera trap image data of wildlife species from a conservancy in Kenya.

Data in brief·2023

相关实验视频

Updated: Jul 8, 2025

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.5K

对于低资源的刚果语语言,语音识别数据集.

Ussen Kimanuka1, Ciira Wa Maina2,3, Osman Büyük4

  • 1Department of Electrical Engineering, Pan African University Institute for Basic Sciences, Technology and Innovation, Nairobi, Kenya.

Data in brief
|December 11, 2023
PubMed
概括

为林加拉语和其他刚果语言创建了新的语音识别数据集. 这些资源有助于为低资源语言开发先进的自动语音识别 (ASR) 模型.

关键词:
自动语音识别自动语音识别跨语言的声学模型.多语言声学模型预先训练有素的模型.自主监督学习学习转移学习转移学习

更多相关视频

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

459
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.0K

相关实验视频

Last Updated: Jul 8, 2025

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.5K
Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

459
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.0K

科学领域:

  • 计算语言学 计算语言学
  • 语音处理 语音处理
  • 低资源的语言技术

背景情况:

  • 大型预训练自动语音识别 (ASR) 模型从转移学习中受益,但需要大量的数据.
  • 许多低资源语言缺乏足够的数据来充分利用转移学习.
  • 基准体对于在数据稀缺的语言环境中推进ASR方法至关重要.

研究的目的:

  • 为刚果民主共和国的低资源语言引入两个新的基准语料库.
  • 促进对刚果语言的单语和多语ASR系统的开发.
  • 为了使林加拉语和其他四种刚果语言的语音识别系统能够进行首次基准测试.

主要方法:

  • 创建了林加拉朗读语音库 (4小时标记音频),拥有多样化的扬声器和口音.
  • 来自广播档案的刚果语音广播集体 (741小时未标记的音频) 的汇编.
  • 监督学习和自我监督学习技术的应用,用于模型开发和基准测试.

主要成果:

  • 开发的公司为ASR研究在资源较少的环境中提供了宝贵的资源.
  • 成功的首次对林加拉语语音识别系统进行基准测试.
  • 为四种刚果语言开发第一个多语言的ASR模型,为9500万人口提供服务.

结论:

  • 发布的数据集对于推进服务不足的语言的ASR研究和开发至关重要.
  • 这些资源为刚果民主共和国改进语音识别技术铺平了道路.
  • 该研究强调了转移学习和新型机构对低资源ASR的潜力.