People talk about coherent episodes of their experience, leading to strong dependencies between words and the contexts in which they appear. Consequently, language within a context is more repetitive and more coherent than language sampled from across contexts.
In this dissertation, I investigated how patterns in infant-directed speech differ under context-sensitive compared to context-independent analysis. In particular, I tested the hypothesis that cues to word boundaries may be clearer within contexts.
Analyzing a large corpus of transcribed infant-directed speech, I implemented three different approaches to defining context: a top-down approach using the occurrence of key words from pre-determined context lists, a bottom-up approach using topic modeling, and a subjective coding approach where contexts were determined by open-ended, subjective judgments of coders reading sections of the transcripts. I found substantial agreement among the context codes from the three different approaches, but also important differences in the proportion of the corpus that was identified by context, the distribution of the contexts identified, and some characteristics of the utterances selected by each approach.
I discuss implications for the use and interpretation of contexts defined in each of these three ways, and the value of a multiple-method approach in the exploration of context. To test the strength of statistical cues to word boundaries in context-specific sub-corpora relative to a context-independent analysis of cues to word boundaries, I used a resampling procedure to compare the segmentability of context sub-corpora defined by each of the three approaches to a distribution of random sub-corpora, matched for size for each context sub-corpus.
Although my analyses confirmed that context-specific sub-corpora are indeed more repetitive, the data did not support the hypothesis that speech within contexts provides richer information about the statistical dependencies among phonemes than is available when analyzing the same statistical dependencies without respect to context. Alternative hypotheses and future directions to further elucidate this phenomenon are discussed. / 2019-02-17
| Identifer | oai:union.ndltd.org:uoregon.edu/oai:scholarsbank.uoregon.edu:1794/22283 |
| Date | 01 May 2017 |
| Creators | Hartman, Rose |
| Contributors | Baldwin, Dare |
| Publisher | University of Oregon |
| Source Sets | University of Oregon |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Rights | All Rights Reserved. |
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