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Alcohol is known to impair fine articulatory control and movements. In drunken speech, incomplete closure of the vocal tract can result in deaffrication of the English affricate sounds /tʃ/ and /ʤ/, spirantization (fricative-like production) of the stop consonants and palatalization (retraction of place of articulation) of the alveolar fricative /s/ (produced as /ʃ/). Such categorical segmental errors have been well-reported. This study employs a phonologicallyinformed neural network approach to estimate degrees of deaffrication of /tʃ/ and /ʤ/, spirantization of /t/ and /d/ and place retraction for /s/ in a corpus of intoxicated English speech. Recurrent neural networks were trained to recognize relevant phonological features [anterior], [continuant] and [strident] in a control speech corpus. Their posterior probabilities were computed over the segments produced under intoxication. The results obtained revealed both categorical and gradient errors and, thus, suggested that this new approach could reliably quantify fine-grained errors in intoxicated speech. 

Alcohol is known to impair fine articulatory control and movements. In drunken speech, incomplete closure of the vocal tract can result in deaffrication of the English affricate sounds /tʃ/ and /ʤ/, spirantization (fricative-like production) of the stop consonants and palatalization (retraction of place of articulation) of the alveolar fricative /s/ (produced as /ʃ/). Such categorical segmental errors have been well-reported. This study employs a phonologicallyinformed neural network approach to estimate degrees of deaffrication of /tʃ/ and /ʤ/, spirantization of /t/ and /d/ and place retraction for /s/ in a corpus of intoxicated English speech. Recurrent neural networks were trained to recognize relevant phonological features [anterior], [continuant] and [strident] in a control speech corpus. Their posterior probabilities were computed over the segments produced under intoxication. The results obtained revealed both categorical and gradient errors and, thus, suggested that this new approach could reliably quantify fine-grained errors in intoxicated speech. Keywords: alcohol, deaffrication, palatalization, retraction, neural network. 

According to the influential continuum model of phonation, only voiced segments can be specified as creaky or breathy. The present study investigated many possible phonetic correlates of the laryngeal contrast in Javanese word-initial prevocalic stop consonants, drawing upon a spoken corpus of more than 180,000 utterances. The results indicate that the laryngeal contrast is cued by voice onset time (VOT) and several acoustic-phonetic properties of the following vowel, including the first formant (F1) in addition to voice source measurements such as H1*-H2* and cepstral peak prominence (CPP). Taken together these findings indicate that Javanese stops can be both voiceless and breathy, supporting a revision of the continuum model in which voicing and other aspects of phonation are decoupled. 

Phonological analyses of long-distance nasal harmony (LDNH) processes classify segments as triggers, undergoers, blockers, or transparent, based primarily on researchers’ subjective judgments of nasality. Using novel field instrumental data from Piaroa (a Jodï-Sáliban language with LDNH), we investigate stop duration, voice onset time (VOT), and nasal and oral airflow during the Piaroa voiceless stops in all-oral environments and continuous nasal harmony spans. We find that nasal harmony has no effect on stop duration and VOT, but voiceless stops in nasal contexts exhibit nasal airflow above an oral baseline at the onset of closure, suggesting that voiceless stops in nasal spans are partial undergoers of LDNH. This partial undergoer behavior is consistent with a model of coactivation of antagonistic gestural specifications for velum activity of the voiceless stop undergoer and the nasal harmony span. Similar voiceless obstruent pre-nasalization is likely widespread cross-linguistically but vastly underreported due to its subtle acoustic effects.