Evaluation of Three Automatic Alignment Tools for the Processing of Non-native French

The production of non-native speech is known to display “cross-language phonetic interference”, which makes such speech un-easy to align and label automatically. Automatic phonetic alignment refers to an automated process whereby software synchronizes speech with its transcription, usually at the phone and word levels. This method has proven useful and reliable for native speech, yet this reliability usually does not extend to non-native speech. This paper proposes to test three major automatic aligners (WebMAUS, MFA and SPPAS) on non-native French uttered by two native speakers of Chinese by comparing them with two manual segmentations. This paper’s goal is to offer non-computer linguists a preliminary investigation on which to rely when choosing a tool for their studies in non-native phonet-ics or language didactics. Results show that the best performing tool for labeling is SPPAS while the best performing tool for both word-and phone-segmentation overall is WebMAUS and MFA the worst.

• Publication year

  2025

• Venue

  Interspeech

• Publication date

  2025-08-17

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.21437/interspeech.2025-716
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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