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Related Concept Videos

Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

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Related Experiment Video

Updated: May 8, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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Published on: September 27, 2024

Using automatic alignment to analyze endangered language data: testing the viability of untrained alignment.

Christian DiCanio1, Hosung Nam, Douglas H Whalen

  • 1Haskins Laboratories, 300 George Street, New Haven, Connecticut 06511, USA. dicanio@haskins.yale.edu

The Journal of the Acoustical Society of America
|August 24, 2013
PubMed
Summary
This summary is machine-generated.

Forced alignment tools can help segment endangered language data, even with different training languages. Using detailed phone sets improved accuracy for phonetic analysis, making research more efficient.

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Area of Science:

  • Linguistics
  • Computational Linguistics
  • Phonetics

Background:

  • Documenting endangered languages is crucial but faces challenges in phonetic analysis.
  • Segmentation of large phonetic corpora is a significant bottleneck for researchers.

Purpose of the Study:

  • To assess the effectiveness of forced alignment tools for segmenting small endangered language datasets.
  • To determine if context-aware phone sets improve alignment accuracy compared to general ones.
  • To evaluate the performance of English-trained forced aligners on Yoloxóchitl Mixtec data.

Main Methods:

  • Two forced alignment tools (hmalign, p2fa) trained on English were tested.
  • Corpus data from Yoloxóchitl Mixtec was used for accuracy assessment.
  • Agreement performance was measured within a 30 ms window.

Main Results:

  • Good overall agreement was achieved: 70.9% for hmalign and 65.7% for p2fa within 30 ms.
  • Segmental and tonal categories impacted accuracy.
  • The hmalign aligner benefited from including additional stop allophones in its phone set.

Conclusions:

  • Forced alignment tools show potential for efficient phonetic analysis of small corpora.
  • Context-aware phone sets offer better agreement than general phone sets.
  • Cross-linguistic application of forced alignment is feasible for endangered language documentation.