Interpreting the order of operations in a sociophonetic analysis
Bibliographic Data
| ID | 21226591 |
|---|---|
| Authors | Joseph A Stanley (0000-0002-9185-0048, Brigham Young University, corresponding author) |
| Year | 2022 |
| Volume | 8 |
| Issue | 1 |
| Pages | 279-289 |
| Publication date | 2022-12-29 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Linguistics Vanguard (JOURNAL) |
| Journal identifiers | ISSN: 2199-174X • E-ISSN: 2199-174X |
| Publisher | Walter de Gruyter GmbH (PUBLISHER • DE) |
| DOI | 10.1515/lingvan-2022-0065 |
| OpenAlex | W4311312889 |
| Language | EN |
| Citations received | 1 |
| References cited | 10 |
Sociophonetic data analysis involves a pipeline of processing steps to convert a raw spreadsheet of acoustic measurements to interpretable results. While most studies report the steps used in their pipeline, very few explicitly report their order in which those steps were applied. This study analyzes a dataset containing vowel formant data from 53 speakers by processing it 5,040 unique ways, each representing a different permutation of seven processing steps. To analyze the effect that an order has on the overall results, pairs of pipelines that differed only by swapping two adjacent steps were compared. The most important steps in the pipeline were when normalization happened, how outliers were detected, and when good data was excluded. This study illustrates what happens when these steps are rearranged relative to each other in order to justify and recommend the following order of operations: classifying allophones, removing outliers, normalizing, and then subsetting
Data mining · Data Processing · Database · Formant · Natural language processing · Outlier · Programming language · Raw data · Speech recognition · Vowel · Computer Science · Linguistic Variation and Morphology · Music and Audio Processing · Speech and Audio Processing · Artificial Intelligence
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |