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The realization of tones in spontaneous spoken Taiwan Mandarin: a corpus-based survey and theory-driven computational modeling

arXiv 2503.23163 ↗First posted 29 Mar 2025cs.CLcited by 7

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Abstract (arXiv)

A growing body of literature has demonstrated that semantics can co-determine fine phonetic detail. However, the complex interplay between phonetic realization and semantics remains understudied, particularly in pitch realization. The current study investigates the tonal realization of Mandarin disyllabic words with all 20 possible combinations of two tones, as found in a corpus of Taiwan Mandarin spontaneous speech. We made use of Generalized Additive Mixed Models (GAMs) to model f0 contours as a function of a series of predictors, including gender, tonal context, tone pattern, speech rate, word position, bigram probability, speaker and word. In the GAM analysis, word and sense emerged as crucial predictors of f0 contours, with effect sizes that exceed those of tone pattern. For each word token in our dataset, we then obtained a contextualized embedding by applying the GPT-2 large language model to the context of that token in the corpus. We show that the pitch contours of word tokens can be predicted to a considerable extent from these contextualized embeddings, which approximate token-specific meanings in contexts of use. The results of our corpus study show that meaning in context and phonetic realization are far more entangled than standard linguistic theory predicts.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 8 of its 98 references that are in the map. First posted on arXiv 29 Mar 2025.

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8 of 98 references.

References · 8

  1. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
  2. 2016Enriching Word Vectors with Subword Informationcited by 1,583
  3. 2024Word-specific tonal realizations in Mandarincited by 11
  4. 2021Modeling morphology with Linear Discriminative Learning: considerations and design choicescited by 7
  5. 2024Resolving Regular Polysemy in Named Entitiescited by 5
  6. 2024Is deeper always better? Replacing linear mappings with deep learning networks in the Discriminative Lexicon Modelcited by 4
  7. 2024Form and meaning co-determine the realization of tone in Taiwan Mandarin spontaneous speech: the case of T2-T3 and T3-T3 tone sandhicited by 3
  8. 2024A corpus-based investigation of pitch contours of monosyllabic words in conversational Taiwan Mandarincited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 5.

7 papers.