arXiv:2609. 21362v1 Announce Type: new Abstract: Conventional tokenizers represent text as characters or statistically derived subwords, overlooking the internal phonological structure of syllables and often requiring large vocabularies.
arXiv:2606. 17835v1 Announce Type: cross Abstract: This study examines the extent to which the wav2vec2.
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.
The study investigates whether word duration can directly cue word identity in Mandarin Chinese homophones. Participants used duration differences to order homophone pairs, successfully mapping shorter durations to higher-frequency words even under high noise or with no other cues. These findings suggest that word duration is a phonetic detail incorporated into lexical representations.
The study evaluates phonologically informed tokenization for German speech recognition using a wav2vec 2.0 backbone fine‑tuned with CTC. Three tokenizer families—pretrained multilingual characters, data‑driven BPE, and phonologically informed units from syllabification and grapheme‑to‑phoneme conversion—are compared across 40 fine‑tunes on three German test sets (in‑domain read, dialectal spontaneous, and standard spontaneous speech). Results show that phonologically informed tokenizers match BPE and character baselines in‑domain, but under domain shift their performance depends on vocabulary size rather than linguistic variation, with syllable‑aware tokenization benefiting dialectal and spontaneous speech at small vocabularies; a phoneme‑level confusion analysis indicates that the acoustic encoder dominates error patterns.
arXiv:2610.08879v1 Announce Type: new Abstract: Pretraining strategies significantly impact the quality of language models, yet existing comparisons of Masked Language Modeling (MLM), Whole Word Mask...
arXiv:2601.09050v2 Announce Type: replace Abstract: Tonal low-resource languages are widely spoken but remain underserved by modern speech technologies. A central challenge is learning speech represe...
arXiv:2609.36131v1 Announce Type: new Abstract: Sinhala Sandhi splitting recovers the constituent words or morphemes hidden inside a phonologically merged surface form. The task is important for Sinh...
arXiv:2607. 01965v1 Announce Type: cross Abstract: Neural TTS systems can sound natural across languages, but naturalness does not guarantee the preservation of sound contrasts that distinguish words from their grammatical forms.
arXiv:2510.22172v2 Announce Type: replace-cross Abstract: The Continuous Integrate-and-Fire (CIF) mechanism provides effective alignment for non-autoregressive (NAR) speech recognition. This mechanis...
Neural TTS systems can sound natural across languages, but naturalness does not guarantee the preservation of sound contrasts that distinguish words from their grammatical forms. Standard metrics like MOS do not test for this.
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...