Database of Mandarin Neighborhood Statistics
14903Authors
nan
Abstract
AbstractIn the design of controlled experiments with language stimuli, researchers from psycholinguistic, neurolinguistic, and related fields, require language resources that isolate variables known to affect language processing. This article describes a freely available database that provides word level statistics for words and nonwords of Mandarin, Chinese. The featured lexical statistics include subtitle corpus frequency, phonological neighborhood density, neighborhood frequency, and homophone density. The accompanying word descriptors include pinyin, ascii phonetic transcription (sampa), lexical tone, syllable structure, dominant PoS, and syllable, segment and pinyin lengths for each phonological word. It is designed for researchers particularly concerned with language processing of isolated words and made to accommodate multiple existing hypotheses concerning the structure of the Mandarin syllable. The database is divided into multiple files according to the desired search criteria: 1) the syllable segmentation schema used to calculate density measures, and 2) whether the search is for words or nonwords. The database is open to the research community at https://github.com/karlneergaard/Mandarin-Neighborhood-Statistics.
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Database of Mandarin Neighborhood Statistics Karl Neergaard, Hongzhi Xu, Chu-Ren Huang The Hong Kong Polytechnic University 11 Yuk Choi Rd. Hunghom, Hong Kong E-mail: karlneergaard@gmail.com, hongz.xu@gmail.com, churen.huang@polyu.edu.hk Abstract In the design of controlled experiments with language stimuli, researchers from psycholinguistic, neurolinguistic, and related fields, require language resources that isolate variables known to affect language processing. This article describes a freely available database that provides word level statistics for words and nonwords of Mandarin, Chinese. The featured lexical statistics include subtitle corpus frequency, phonological neighborhood density, neighborhood frequency, and homophone density. The accompanying word descriptors include pinyin, ascii phonetic transcription (sampa), lexical tone, syllable structure, dominant PoS, and syllable, segment and pinyin lengths for each phonological word. It is designed for researchers particularly concerned with language processing of isolated words and made to accommodate multiple existing hypotheses concerning the structure of the Mandarin syllable. The database is divided into multiple files according to the desired search criteria: 1) the syllable segmentation schema used to calculate density measures, and 2) whether the search is for words or nonwords. The database is open to the research community at https://github.com/karlneergaard/Mandarin-Neighborhood-Statistics. Keywords: lexical statistics, phonological neighborhood density, Mandarin, Chinese 1. Introduction Essential to conducting controlled language experiments is the availability of linguistic tools that provide word level statistics. While a frequency list of word occurrence might be the primary goal of many databases used by psycholinguists, neighborhood density measures have become instrumental in studies of language processing. Phonological neighborhood density (PND), which is the calculation of whole word sound similarity through the addition, deletion or substitution of a single phoneme, has been extensively studied, which explains the large number of resources available, for example, in English (N-Watch: Davis, 2005; IPhod: Vaden et al., 2009); Spanish (BuscaPalabras: Davis & Perea, 2005), French (Lexique: New et al., 2001) and representing multiple European languages (Clearpond: Marian et al., 2012). For Mandarin, while frequency measures have come from large-scale corpora (e.g., Sinica Corpus: Chen et al., 1996; Lancaster Corpus of Mandarin Chinese (LCMC): McEnery & Xiao, 2003; The language corpus system of Modern Chinese Study (LCSMCS): Sun, et al., 1997) or more recently a movie subtitle corpus (Subtlex-CH: Cai & Brysbaert, 2010), there is to date no resource available for neighborhood density measures. The current paper introduces a freely available database of lexical statistics including neighborhood density measures for Mandarin, Chinese. A principle goal of the current database is to create a centralized tool for the testing of multiple hypotheses on the nature of the Mandarin mental lexicon. The area in which researchers have widely disagreed is in the phonological content of the Mandarin syllable. Depending on the area of research being explored, researchers will claim that the base syllable consists of either three or four segments. The four-segments approach consists of a maximal syllable of CVVX, wherein the C corresponds to initial consonants, the following V is commonly referred to as the medial glide, the second V allows for monophthongs, and the final X corresponds either to the …
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Labeled Text
AbstractIn the design of controlled experiments with language stimuli, researchers from psycholinguistic, neurolinguistic, and related fields, require language resources that isolate variables known to affect language processing. This article describes a freely available database that provides word level statistics for words and nonwords of Mandarin, Chinese. The featured lexical statistics include subtitle corpus frequency, phonological neighborhood density, neighborhood frequency, and homophone density. The accompanying word descriptors include pinyin, ascii phonetic transcription (sampa), lexical tone, syllable structure, dominant PoS, and syllable, segment and pinyin lengths for each phonological word. It is designed for researchers particularly concerned with language processing of isolated words and made to accommodate multiple existing hypotheses concerning the structure of the Mandarin syllable. The database is divided into multiple files according to the desired search criteria: 1) the syllable segmentation schema used to calculate density measures, and 2) whether the search is for words or nonwords. The database is open to the research community at
Publication Details
- Paper ID:
- 14903
- Year:
- 2016
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan