Direct cueing of word identity through word duration: evidence from Mandarin homophones
Authors: Xiaomeng Zhu, Megan Niu, Jason Shaw, Kevin Tang
Organizations: Department of Linguistics, Yale University, New Haven, USA · Department of English Language and Linguistics, Institute of English and American Studies, Faculty of Arts and Humanities, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany · Also at: Department of Linguistics, University of Florida, Gainesville, Florida, 32611-5454, United States of America
While there is increasing evidence that words are stored in the mental lexicon with some phonetic detail, there are open questions about exactly which phonetic details are stored and whether they are functionally relevant for spoken word recognition. Word-level phonetic cues, such as word duration, provide an appropriate test case. Across languages, including Mandarin Chinese, high frequency words are shorter than low frequency words. Using a homophone ordering task, we investigate whether differences in word duration impact word recognition. Mandarin Chinese was examined since it has abundant disyllabic homophones. Our results indicate that participants were able to use word duration to recognize the order of homophone pairs, selected to vary in lexical frequency. Both with high noise levels and when no other cues were available, participants mapped the shorter duration auditory stimulus to the higher frequency word. The results provide evidence that word duration can directly cue the identity of words, suggesting that it may be a phonetic detail incorporated into the lexical representation. We discuss this direct cueing account alongside alternative accounts of how word duration may modulate word recognition.
Figures & tables
Account
(i) Context integration
(ii) Spectral integration
(iii) Direct cueing
Prediction
At chance
At chance
Above chance
Table 1: Predictions of the three accounts for our experiments testing homophone identification based on word duration.
Figure 1: Experimental interface in Gorilla showing an example test item (homophone pairs). The instruction at the top says “Which order of words did you hear?”. The left button has a homophone pair of low-high order (frequency), and the right button shows the reverse order.
Parameter
Log-Odds
SE
95% CI
z
p
Intercept
0.11
0.04
[0.03,0.19]
2.81
0.005
Auditory Stimuli [Short–Long]
0.24
0.08
[0.08,0.39]
3.01
0.003
Trial z
0.01
0.04
[−0.07,0.09]
0.26
0.793
Table 2: Results of the logistic mixed-effects regression model predicting homophone-order choice as a function of auditory stimulus type and standardized trial order in Experiment 1.
Parameter
Log-Odds
SE
95% CI
z
p
Intercept
0.01
0.05
[−0.08,0.10]
0.25
0.804
Auditory Stimuli [Short–Long]
0.20
0.08
[0.05,0.35]
2.60
0.009
Trial z
0.00946
0.04
[−0.07,0.08]
0.25
0.805
Table 3: Results of the logistic mixed-effects regression model predicting homophone-order choice as a function of auditory stimulus type and standardized trial order in Experiment 2.
Table 4: Results of the logistic mixed-effects regression model predicting homophone-order choice from auditory stimulus type, experiment, their interaction, and standardized trial order. Categorical predictors were coded using −0.5 and +0.5 contrasts.
The distribution of spoken word duration of English homophones is known to co-vary with frequency of use. This study investigates whether other aspects of the phonetic realization of homophones also differ. A series of quantitative investigations of 14,000 homophone tokens in American television news broadcasts revealed that the tokens of homophone pairs such as weight and wait have different phonetic realizations, and that these can be predicted from their meanings in utterance context. These systematic differences remain even when taking duration-related variation into account. Time-normalized spectrograms emerged as an excellent tool for probing the fine details of phonetic realization, and obviate the need for phonetic transcriptions, which inevitably hide the phonetic truth from our eyes.
Yu-Hsiang Tseng, Mirjam T. C. Ernestus, Louis F. M. ten Bosch +1
University of Tübingen, Germany · Radboud University, the Netherlands
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. We show that CEs indeed are predictive for duration, above chance level, not only at the type level, but also at the level of individual tokens, as indicated by the results obtained with the type-wise and token-wise permutation baselines. We also show that the predicted durations are sufficiently precise to back-transform predicted f0 contours in [0,1] normalized time to contours on the ms time scale. The resulting predicted contours approximate empirical contours and also outperform a permutation baseline.
Xiaoyun Jin, Mirjam Ernestus, R. Harald Baayen
Quantitative Linguistik, University of Tuebingen, Germany · Center for Language Studies, Radboud University, 6525 HT Nijmegen, The Netherlands
Consonants contribute unequally to whether a word is understood. Given the limited time available for therapy, ranking consonants by contribution to intelligibility helps prioritize intervention targets in motor speech disorders. However, measuring this contribution relies on perceptual studies that are difficult to scale. This paper presents a scalable method that measures consonant contribution using acoustic masking. We silence one consonant at a time in an isolated word and test whether an automatic speech recognition (ASR) model still recognizes the word. We define a consonant's contribution score as the proportion of its masked instances for which the word becomes misrecognized, which we refer to as the mask-induced misrecognition rate (MMR). We relate MMR to two linguistic factors previously reported to correlate with consonant contribution, namely phoneme frequency and functional load. We apply this analysis across four languages, English, Spanish, German, and Czech, using three ASR architectures, MMS (encoder-only), Whisper (encoder-decoder), and Qwen3-ASR (LLM-based). Using partial Spearman correlations, we find that phoneme frequency correlates negatively with MMR while functional load correlates positively. In other words, more frequent consonants are less disruptive when masked, whereas consonants carrying more lexical contrast are more disruptive. Further cross-language analysis shows that consonant rankings agree only partially across languages, indicating that consonant contribution is language-dependent.
Eunjung Yeo, Kwanghee Choi, Krupaben Kothadia +4
University of Texas at Austin, USA · Arizona State University, USA · Carnegie Mellon University, USA