Phonetic transcription of spontaneous children's speech with the aid of software: a systematic review

Debora Tomazi Moreira Caumo,
Márcio Pezzini França,
Clécio Homrich da Silva
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Abstract

The aim of the study was to identify, synthesize and classify the software currently available that can help in the task of phonetic transcription of the spontaneous speech of pre-school children to evaluate the development of children's language. A systematic review was performed for articles published, for the 10-year period (June 2010 to June 2020), without restrictions as to location and language, using the Cochrane, Pubmed and Web of Science databases. The terms used in the search strategies were "phonological", "phonetic", "transcription", "computer" and "software". The studies were selected by two independent reviewers using pre-defined search strategies. In the initial search, after the exclusion of duplicates, 534 articles were found. By reading their titles and abstracts, 46 articles related to the theme were left, which were then read in full. After reading, 24 articles were included in the study. The results revealed a total of seven software available for the phonetic transcription of spontaneous speech from preschoolers used for different analyses: LENA and Timestamper (for babbling and pre-linguistic vocalizations), ELAN (for gestural communication, extralinguistic elements and the situational context), Phon (for phonetic and phonological analyses), CLAN and SALT (for morphosyntactic, grammatical and semantic aspects) and Praat (for acoustic measurements). Through this systematic review, it can be concluded that there are advantages to using software for phonetic transcription, sample storage, and child language analysis, especially concerning standardization and reliability for spontaneous speech samples. Phonetic transcription still relies on the ability and subjectivity of a human transcriber. The tools found in the software provide support to facilitate using phonetic symbols, audio segmentation and pairing to writing, and analysis of speech data.

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