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Related Concept Videos

Components of Language01:24

Components of Language

329
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
329
Language Development01:22

Language Development

403
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
403
Sample Preparation for Analysis: Advanced Techniques01:08

Sample Preparation for Analysis: Advanced Techniques

398
Accurate analysis of complex samples often requires advanced preparation techniques to achieve reliable and reproducible results. Samples containing inorganic or organic materials can be challenging to dissolve or decompose effectively. Standard sample preparation methods include acid digestion, fusion, dry ashing, and wet digestion.
Acid digestion with strong acids is commonly used to dissolve inorganic materials that are insoluble (do not dissolve) in water. This method can be useful for...
398
Sample Preparation for Analysis: Overview01:21

Sample Preparation for Analysis: Overview

266
Sample preparation is an essential step in the analytical process. It involves preparing a sample so that it can be analyzed accurately. The goal is to extract the analyte, the substance you want to measure, from the sample while removing any components that may interfere with the analysis. Sample preparation techniques vary depending on the physical state of the sample.
Bulk or large solid samples are typically reduced in size using grinding, crushing, or milling techniques to increase the...
266
Mass Analyzers: Overview01:13

Mass Analyzers: Overview

741
The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
741
Sample Handling01:02

Sample Handling

127
Transportation of samples from the collection point to the laboratory, as well as storage and preservation techniques, are crucial for maintaining sample integrity and ensuring accurate and reliable test results.
Samples should be transported carefully from collection points to the laboratory. They should be properly sealed and clearly labeled to prevent cross-contamination. To preserve the sample integrity, optimal temperature conditions during transport are essential. This could involve using...
127

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Related Experiment Video

Updated: Jul 26, 2025

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

475

Automation of Language Sample Analysis.

Houjun Liu1, Brian MacWhinney2, Davida Fromm2

  • 1The Nueva School, San Mateo, CA.

Journal of Speech, Language, and Hearing Research : JSLHR
|June 22, 2023
PubMed
Summary
This summary is machine-generated.

Automating language sample analysis (LSA) with the Batchalign pipeline significantly reduces transcription time by up to 75%. This method provides accurate, time-aligned transcripts for clinical practice and research.

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Area of Science:

  • Linguistics
  • Computational Linguistics
  • Speech-Language Pathology

Background:

  • Language sample analysis (LSA) is crucial for clinical practice and research.
  • Transcription is a time-intensive bottleneck in LSA.

Purpose of the Study:

  • To introduce Batchalign, an automated pipeline for LSA transcription.
  • To reduce the time and effort required for LSA data processing.

Main Methods:

  • The Batchalign pipeline integrates automatic speech recognition, tokenization, correction, speaker ID assignment, and forced alignment.
  • It produces transcripts in Codes for the Human Analysis of Talk (CHAT) format with time alignments and morphosyntactic analysis.
  • Minimal human intervention is needed for final checks.

Main Results:

  • Word error rates were low (2.4%-3.4%) for adults with and without language disorders.
  • Utterance tokenization and word-level diarization accuracy were high.
  • Human transcriber time was reduced by up to 75%, with full adherence to CHAT format.

Conclusions:

  • Batchalign dramatically shortens the data collection to analysis timeline.
  • The pipeline offers superior output compared to manual transcription, facilitating LSA use.