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
The study examines how English homophones—words that sound identical but have different meanings—are pronounced differently in spoken language. Analyzing 14,000 homophone tokens from American television news, researchers found that pairs such as "weight" and "wait" exhibit distinct phonetic realizations that can be predicted from their contextual meanings, even after controlling for word duration. Time‑normalized spectrograms proved effective for detecting these subtle differences without relying on phonetic transcriptions.
arXiv:2611.05803v1 Announce Type: new
Abstract: How much phonological knowledge do language models (LMs) possess about Chinese characters, and how is this knowledge represented and used? We introduce...
By Xiaozhe Ji, Renfen Hu, Hai Hu
Time-normalized f0 contours of Mandarin words in conversational speech have been shown to be predictable in part from their contextualized embeddings (CEs). The present study investigates whether CEs also predict spoken word duration for 7470 tokens of Mandarin monosyllabic CV words extracted from a Mandarin corpus of spontaneous speech.
The neutral, or floating, tone of Mandarin Chinese is a tone with an enigmatic set of properties. It has been described as a reduced tone, or as a tone that sometimes is lexically fixed but that can also be toneless.
arXiv:2610.04898v2 Announce Type: replace-cross
Abstract: This study analyzes the predictive power of LM-derived, token-level surprisal on Mandarin Chinese reading times. We first propose the Shortes...
By Hongao Zhu, Muxiaoqiao Xu, Yikang Liu, Siyuan Song, Yuxia Wang, Byung-Doh Oh, Hai Hu