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DAPPr : A ( semi-) automated tool for pitch annotation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Grabowski, Emily McPherson, Laura |
| Copyright Year | 2019 |
| Abstract | This paper describes a novel computational toolkit for tonal analysis: DAPPr (Discrete Annotations for Pitch and Prosody). In particular, in this paper, we describe a first-pass method for automatically extracting target segments for analysis using a trained deep learning neural network. This automatic segment extractor is designed to work languageindependently with minimal or zero training data. Together with the already-implemented DAPPr suite, these tools produce discrete pitch annotations that are consistent, objective, and compatible with other techniques and tools for analysis. While this tool was designed with tone languages in mind, the segment extraction and pitch analysis methods are relevant to the study of prosody more generally or even simply for automatic vowel detection. The aim of this analytical suite is to promote the inclusion of objective, replicable pitch data in documentary, descriptive, or theoretical materials. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://icphs2019.org/icphs2019-fullpapers/pdf/full-paper_345.pdf |
| Alternate Webpage(s) | http://www.assta.org/proceedings/ICPhS2019/papers/ICPhS_1753.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
