Characteristics of stop releases in American English spontaneous speech

Lisa Davidson

    Research output: Contribution to journalArticle

    Abstract

    This study examines the factors affecting the production of stop releases in American English spontaneous speech. Previous research has shown that releases are conditioned by phonetic and social factors. However, previous studies either rely exclusively on read speech, or for sociolinguistic studies, focus on phrase-final stops. In this study, spontaneous speech is collected from two sources: interviews from the non-profit StoryCorps project and from sentences spontaneously generated in a picture description task. Stop releases were examined before obstruents and nasals in word-medial position (e.g. rugby), word-final, phrase-medial position (e.g. They crack nuts), and pre-pausally (e.g. I look up). Phonetic factors taken into account include identity of the stop, directionality of place of articulation in the consonant cluster (front-to-back vs. back-to-front) and manner of C2. For the StoryCorps data, race of the speaker was also found to be an important predictor. Results showed that approximately a quarter of the stops followed by a consonant were released, but release was strongly affected by the place of the stop and the manner of the following consonant. Release of pre-pausal stops differed between black and white speakers; the latter had double the amount of final release. Other realizations of the stops, such as deletion, lenition, and glottalization are also analyzed.

    Original languageEnglish (US)
    Pages (from-to)1042-1058
    Number of pages17
    JournalSpeech Communication
    Volume53
    Issue number8
    DOIs
    StatePublished - Oct 1 2011

    Keywords

    • Articulatory coordination
    • Spontaneous speech
    • Stop releases
    • Stop-consonant sequences

    ASJC Scopus subject areas

    • Software
    • Modeling and Simulation
    • Communication
    • Language and Linguistics
    • Linguistics and Language
    • Computer Vision and Pattern Recognition
    • Computer Science Applications

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