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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
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Systematic Sampling Method01:17

Systematic Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Group Design02:01

Group Design

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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

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Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
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Collection and Analysis of Repeated Speech Samples: Methodological Framework and Example Protocol.

Nicholas Cummins1, Lauren Louise White1, Zahia Rahman1

  • 1Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

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Summary
This summary is machine-generated.

This study introduces a transparent protocol and checklist to improve the reproducibility of speech biomarker research. It aims to standardize data collection and analysis for more reliable health assessments using voice.

Keywords:
health assessmentlongitudinalrepeat recordingsreplicationspeechvoicewithin-speaker variability

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Area of Science:

  • Speech and Language Pathology
  • Biomedical Engineering
  • Computational Linguistics

Background:

  • Speech and language biomarkers offer potential for objective health assessments but face challenges due to high within-individual variability.
  • Inconsistent reporting of speech characteristics in research hinders methodological progress, replication, and biomarker identification.
  • Existing methodologies often fail to adequately account for confounding variables, impacting the reliability of speech-based health assessments.

Purpose of the Study:

  • To present a transparent speech collection and feature extraction protocol and design checklist to facilitate replicable speech research.
  • To demonstrate the feasibility of an in-laboratory protocol designed to minimize confounding factors in healthy speech recordings.
  • To establish a standardized framework for collecting and analyzing speech data for health assessment applications.

Main Methods:

  • Developed a speech collection and feature extraction protocol based on a literature review for controlled investigation of within-individual speech variability.
  • Protocol includes elicitation of read speech, held vowels, and picture descriptions, extracting 14 health-relevant features.
  • Speech data collected using a condenser microphone, 3 smartphones, and a headset for device-specific sensitivity analysis.

Main Results:

  • Collected healthy speech data from 28 individuals (day cohort) and 25 individuals (week cohort) with repeated measures.
  • Collected participant characteristics (sex, age, native language) and contextual data (voice use, intake, emotional state, recording times).
  • Analysis of within-individual variability and device-type sensitivity is ongoing, with results anticipated in 2025.

Conclusions:

  • Variability in speech data collection, processing, and reporting impedes clinical translation of speech biomarkers.
  • A speech curation protocol design checklist is developed to address inconsistencies in research.
  • Standardized reporting and justified protocols are crucial for enabling speech research replication and clinical application.