4,139 research outputs found
Unifying Amplitude and Phase Analysis: A Compositional Data Approach to Functional Multivariate Mixed-Effects Modeling of Mandarin Chinese
Mandarin Chinese is characterized by being a tonal language; the pitch (or
) of its utterances carries considerable linguistic information. However,
speech samples from different individuals are subject to changes in amplitude
and phase which must be accounted for in any analysis which attempts to provide
a linguistically meaningful description of the language. A joint model for
amplitude, phase and duration is presented which combines elements from
Functional Data Analysis, Compositional Data Analysis and Linear Mixed Effects
Models. By decomposing functions via a functional principal component analysis,
and connecting registration functions to compositional data analysis, a joint
multivariate mixed effect model can be formulated which gives insights into the
relationship between the different modes of variation as well as their
dependence on linguistic and non-linguistic covariates. The model is applied to
the COSPRO-1 data set, a comprehensive database of spoken Taiwanese Mandarin,
containing approximately 50 thousand phonetically diverse sample contours
(syllables), and reveals that phonetic information is jointly carried by both
amplitude and phase variation.Comment: 49 pages, 13 figures, small changes to discussio
Pitch ability as an aptitude for tone learning
Tone languages such as Mandarin use voice pitch to signal lexical contrasts, presenting a challenge for second/foreign language (L2) learners whose native languages do not use pitch in this manner. The present study examined components of an aptitude for mastering L2 lexical tone. Native English speakers with no previous tone language experience completed a Mandarin word learning task, as well as tests of pitch ability, musicality, L2 aptitude, and general cognitive ability. Pitch ability measures improved predictions of learning performance beyond musicality, L2 aptitude, and general cognitive ability and also predicted transfer of learning to new talkers. In sum, although certain nontonal measures help predict successful tone learning, the central components of tonal aptitude are pitch-specific perceptual measures
Analyzing Prosody with Legendre Polynomial Coefficients
This investigation demonstrates the effectiveness of Legendre polynomial coefficients representing prosodic contours within the context of two different tasks: nativeness classification and sarcasm detection. By making use of accurate representations of prosodic contours to answer fundamental linguistic questions, we contribute significantly to the body of research focused on analyzing prosody in linguistics as well as modeling prosody for machine learning tasks. Using Legendre polynomial coefficient representations of prosodic contours, we answer prosodic questions about differences in prosody between native English speakers and non-native English speakers whose first language is Mandarin. We also learn more about prosodic qualities of sarcastic speech. We additionally perform machine learning classification for both tasks, (achieving an accuracy of 72.3% for nativeness classification, and achieving 81.57% for sarcasm detection). We recommend that linguists looking to analyze prosodic contours make use of Legendre polynomial coefficients modeling; the accuracy and quality of the resulting prosodic contour representations makes them highly interpretable for linguistic analysis
The phonetics of second language learning and bilingualism
This chapter provides an overview of major theories and findings in the field of second language (L2) phonetics and phonology. Four main conceptual frameworks are discussed and compared: the Perceptual Assimilation Model-L2, the Native Language Magnet Theory, the Automatic Selection Perception Model, and the Speech Learning Model. These frameworks differ in terms of their empirical focus, including the type of learner (e.g., beginner vs. advanced) and target modality (e.g., perception vs. production), and in terms of their theoretical assumptions, such as the basic unit or window of analysis that is relevant (e.g., articulatory gestures, position-specific allophones). Despite the divergences among these theories, three recurring themes emerge from the literature reviewed. First, the learning of a target L2 structure (segment, prosodic pattern, etc.) is influenced by phonetic and/or phonological similarity to structures in the native language (L1). In particular, L1-L2 similarity exists at multiple levels and does not necessarily benefit L2 outcomes. Second, the role played by certain factors, such as acoustic phonetic similarity between close L1 and L2 sounds, changes over the course of learning, such that advanced learners may differ from novice learners with respect to the effect of a specific variable on observed L2 behavior. Third, the connection between L2 perception and production (insofar as the two are hypothesized to be linked) differs significantly from the perception-production links observed in L1 acquisition. In service of elucidating the predictive differences among these theories, this contribution discusses studies that have investigated L2 perception and/or production primarily at a segmental level. In addition to summarizing the areas in which there is broad consensus, the chapter points out a number of questions which remain a source of debate in the field today.https://drive.google.com/open?id=1uHX9K99Bl31vMZNRWL-YmU7O2p1tG2wHhttps://drive.google.com/open?id=1uHX9K99Bl31vMZNRWL-YmU7O2p1tG2wHhttps://drive.google.com/open?id=1uHX9K99Bl31vMZNRWL-YmU7O2p1tG2wHAccepted manuscriptAccepted manuscrip
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