Vocabulary Size Influences Spontaneous Speech in Native Language Users: Validating the Use of Automatic Speech Recognition in Individual Differences Research
Autor: | Suzanne R. Jongman, Florian Hintz, Yung Han Khoe |
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Rok vydání: | 2020 |
Předmět: |
Adult
Male 050101 languages & linguistics Linguistics and Language Vocabulary Sociology and Political Science Adolescent Speech recognition First language media_common.quotation_subject Individuality Language Development 050105 experimental psychology Language and Linguistics Task (project management) Speech and Hearing Young Adult Natural (music) Humans Speech 0501 psychology and cognitive sciences media_common Language Tests Psycholinguistics Language production 05 social sciences General Medicine Speech Perception Female Transcription (software) Psychology Natural language Sentence |
Zdroj: | Language and Speech |
ISSN: | 1756-6053 |
Popis: | Previous research has shown that vocabulary size affects performance on laboratory word production tasks. Individuals who know many words show faster lexical access and retrieve more words belonging to pre-specified categories than individuals who know fewer words. The present study examined the relationship between receptive vocabulary size and speaking skills as assessed in a natural sentence production task. We asked whether measures derived from spontaneous responses to everyday questions correlate with the size of participants’ vocabulary. Moreover, we assessed the suitability of automatic speech recognition (ASR) for the analysis of participants’ responses in complex language production data. We found that vocabulary size predicted indices of spontaneous speech: individuals with a larger vocabulary produced more words and had a higher speech-silence ratio compared to individuals with a smaller vocabulary. Importantly, these relationships were reliably identified using manual and automated transcription methods. Taken together, our results suggest that spontaneous speech elicitation is a useful method to investigate natural language production and that automatic speech recognition can alleviate the burden of labor-intensive speech transcription. |
Databáze: | OpenAIRE |
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