arXiv Computation and Language

Speaker-Specific and Language-Dependent Temporal Organization in Bilingual Political Speech

The study investigates how bilingual politicians structure the timing of their speeches in Luxembourgish and French, analyzing 400 sentences from ten speakers. Rhythm metrics were computed for consonants and vowels, revealing that consonant patterns are largely speaker-specific while vowel patterns are strongly influenced by language choice. French tokens exhibited longer, more variable vowels and vocalic intervals, whereas consonant timing differences were smaller, with no significant language-by-gender interactions.

arXiv Computation and Language
Sep 16

Speaker or Language? Explaining Variance in Charismatic Prosody Across Luxembourgish and French

The study examined 400 utterances from 10 politicians speaking in both Luxembourgish and French to determine how much of charismatic prosody is due to speaker identity versus language. Mixed‑effects modeling revealed that speaker identity explained most of the variance, while language contributed less but still produced systematic differences: French speech had higher shimmer and phrase‑final F0, suggesting a polite, respectful tone, whereas Luxembourgish speech showed stronger mid‑frequency spectral energy, indicating a more vocally present profile. These acoustic patterns reflect the sociolinguistic roles of Luxembourgish as an informal identity language and French as a high‑prestige institutional variety.

By Nina Hosseini-Kivanani, Nafiseh Taghva, Peter Gilles, Oliver Niebuhr
arXiv AI
Sep 17

Evolution of US Oral Political Language

The study analyzes oral political language in U.S. presidential debates from 1960 to 2024, focusing on 19 candidates. It finds a clear trend toward simplification: sentence length and complex terms have decreased, while emotional tone has risen and logical, rational content has diminished. The research also explores whether specific presidents exhibit unique stylistic traits and whether language patterns correlate with electoral success.

By Jacques Savoy
arXiv AI
Sep 1

Using Prosody to Predict Syntactic Structure

arXiv:2608.30260v1 Announce Type: cross Abstract: While it is well-established that prosody carries crucial cues for syntactic structure, the degree and nature of correspondence between these two dom...

By Junghyun Min, Alex Warstadt, Tamar I. Regev, Tiago Pimentel, Ethan Gotlieb Wilcox
arXiv Computation and Language
Aug 31

Is Prosody Lost in Translation? Fine-Grained Cross-Lingual Prosody Similarity Across Languages

This paper investigates whether prosodic features—pitch, energy, and timing—are preserved when speech is translated between languages. Using multilingual dubbing data for English‑German, English‑Spanish, and English‑French pairs, the authors conduct a fine‑grained cross‑lingual analysis to quantify similarities and differences in prosody. The study identifies inherent cross‑lingual correlations in prosodic structure and explores how linguistic and alignment factors influence these patterns.

By Haopeng Xie, Ismail Rasim Ulgen, Sofia Son, Berrak Sisman, Philipp Koehn
arXiv AI
Jun 16

P3B3: A Multi-Turn Conversational Benchmark for Measuring European and Brazilian Portuguese Variety Bias in LLMs

arXiv:2606. 16753v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become embedded in everyday communication, capturing regional linguistic variation is essential for reliable and equitable language use.

By Rafael Ferreira, In\^es Vieira, In\^es Calvo, James Furtado, Iago Paulo, Diogo Tavares, Diogo Gl\'oria-Silva, David Semedo, Jo\~ao Magalh\~aes
arXiv Computation and Language
Aug 28

Letters hide the truth from our eyes: English homophones have meaningfully different phonetic realizations

The study examines whether English homophones differ in phonetic realization beyond spoken word duration. Analyzing 14,000 homophone tokens from American television news, it finds that pairs such as "weight" and "wait" exhibit distinct phonetic patterns that can be predicted from their meanings in context. These differences persist even after controlling for duration, and time‑normalized spectrograms prove effective for detecting such fine‑grained phonetic variation without relying on phonetic transcriptions.

By Yu-Hsiang Tseng, Mirjam T. C. Ernestus, Louis F. M. ten Bosch, R. Harald Baayen
arXiv Computation and Language
Sep 18

Evaluating Bias in Phoneme-Based Automatic Speech Recognition Systems: An Analysis of IPA Transcription Models

The paper evaluates bias in phoneme-based automatic speech recognition (ASR) systems, focusing on WhisperIPA and ZIPA, which produce International Phonetic Alphabet (IPA) transcriptions. Using multilingual speech corpora and demographically annotated English datasets, the authors compare model-generated IPA against grapheme-to-phoneme (G2P) outputs with both standard phoneme error rate (PER) and a new Soft PER metric that allows linguistically similar substitutions. The study finds persistent disparities across language, gender, accent, ethnicity, and age, even when accounting for acceptable phonemic variation.

By Maneesha Rani Saha, Catherine Bao, Neal Patwari