Improving Audio-Visual Speech Recognition by Lip-Subword Correlation Based Visual Pre-training and Cross-Modal Fusion Encoder

In recent research, slight performance improvement is observed from automatic speech recognition systems to audio-visual speech recognition systems in the end-to-end framework with low-quality videos. Unmatching convergence rates and specialized input representations between audio and visual modalities are considered to cause the problem. In this paper, we propose two novel techniques to improve audio-visual speech recognition (AVSR) under a pre-training and fine-tuning training framework. First, we explore the correlation between lip shapes and syllable-level subword units in Mandarin to establish good frame-level syllable boundaries from lip shapes. This enables accurate alignment of video and audio streams during visual model pre-training and cross-modal fusion. Next, we propose an audio-guided cross-modal fusion encoder (CMFE) neural network to utilize main training parameters for multiple cross-modal attention layers to make full use of modality complementarity. Experiments on the MISP2021-AVSR data set show the effectiveness of the two proposed techniques. Together, using only a relatively small amount of training data, the final system achieves better performances than state-of-the-art systems with more complex front-ends and back-ends.Comment: 6 pages, 2 figures, published in ICME202

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 $F_0$) 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 $F_0$ 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

Script Effects as the Hidden Drive of the Mind, Cognition, and Culture

This open access volume reveals the hidden power of the script we read in and how it shapes and drives our minds, ways of thinking, and cultures. Expanding on the Linguistic Relativity Hypothesis (i.e., the idea that language affects the way we think), this volume proposes the “Script Relativity Hypothesis” (i.e., the idea that the script in which we read affects the way we think) by offering a unique perspective on the effect of script (alphabets, morphosyllabaries, or multi-scripts) on our attention, perception, and problem-solving. Once we become literate, fundamental changes occur in our brain circuitry to accommodate the new demand for resources. The powerful effects of literacy have been demonstrated by research on literate versus illiterate individuals, as well as cross-scriptal transfer, indicating that literate brain networks function differently, depending on the script being read. This book identifies the locus of differences between the Chinese, Japanese, and Koreans, and between the East and the West, as the neural underpinnings of literacy. To support the “Script Relativity Hypothesis”, it reviews a vast corpus of empirical studies, including anthropological accounts of human civilization, social psychology, cognitive psychology, neuropsychology, applied linguistics, second language studies, and cross-cultural communication. It also discusses the impact of reading from screens in the digital age, as well as the impact of bi-script or multi-script use, which is a growing trend around the globe. As a result, our minds, ways of thinking, and cultures are now growing closer together, not farther apart. ; Examines the origin, emergence, and co-evolution of written language, the human mind, and culture within the purview of script effects Investigates how the scripts we read over time shape our cognition, mind, and thought patterns Provides a new outlook on the four representative writing systems of the world Discusses the consequences of literacy for the functioning of the min

Tonal Adaptation of Loanwords in Mandarin: Phonology and Beyond

This study examines the tonal adaptation of English and Japanese loanwords in Mandarin, and considers data collected from different types of sources. The purpose overall is to identify the mechanisms underlying the adaptation processes by which tone is assigned, and to check if the same mechanisms are invoked regardless of donor languages and source types. Both corpus and experimental methods were utilized to survey a broad sampling of borrowings and a wide array of syllable types that target specific phonetic properties. To maximally rule out the effect of semantic tingeing, this study examined English place names that were extracted from a dictionary and from online travel blogs. And to explore how semantic association might interfere with the adaptation processes, this study also investigated a separate corpus of Japanese manga role names and brand names. Revisiting discussions in previous studies about how phonetic properties of the source form might affect tonal assignments in the adapted forms, this study also included an expanded reanalysis of adaptations elicited in an experimental setting. Observations made in the study suggest that the primary mechanisms behind tonal assignments for loanwords in Mandarin operate at a level beyond any usual phonological concerns: the adaptation processes are heavily reliant on factors that are inherent to Mandarin lexical distributions, such as tone probability and character frequency. Adapters apparently utilize their tacit knowledge about such distributional properties when assigning tones. Also crucial to the tonal assignment mechanism is the seeking of appropriate characters based on their meanings, either to avoid unintended readings of loanwords or to form desired interpretations. Such adaptation mechanisms are mainly attributable to the morpho-syllabic nature of the Chinese writing system, the language’s high productivity of compound words, and its high incidence of homophony. Also noted in the study is the influence of prescriptive conventions formulated for formally established loanwords. Research findings reported in this study highlight such non-phonological aspects of loanword adaptation, especially the role of the writing system, that have been underestimated to date in the field of loanword phonology and cross-linguistic studies of loanword typology

A computational model for studying L1’s effect on L2 speech learning

abstract: Much evidence has shown that first language (L1) plays an important role in the formation of L2 phonological system during second language (L2) learning process. This combines with the fact that different L1s have distinct phonological patterns to indicate the diverse L2 speech learning outcomes for speakers from different L1 backgrounds. This dissertation hypothesizes that phonological distances between accented speech and speakers' L1 speech are also correlated with perceived accentedness, and the correlations are negative for some phonological properties. Moreover, contrastive phonological distinctions between L1s and L2 will manifest themselves in the accented speech produced by speaker from these L1s. To test the hypotheses, this study comes up with a computational model to analyze the accented speech properties in both segmental (short-term speech measurements on short-segment or phoneme level) and suprasegmental (long-term speech measurements on word, long-segment, or sentence level) feature space. The benefit of using a computational model is that it enables quantitative analysis of L1's effect on accent in terms of different phonological properties. The core parts of this computational model are feature extraction schemes to extract pronunciation and prosody representation of accented speech based on existing techniques in speech processing field. Correlation analysis on both segmental and suprasegmental feature space is conducted to look into the relationship between acoustic measurements related to L1s and perceived accentedness across several L1s. Multiple regression analysis is employed to investigate how the L1's effect impacts the perception of foreign accent, and how accented speech produced by speakers from different L1s behaves distinctly on segmental and suprasegmental feature spaces. Results unveil the potential application of the methodology in this study to provide quantitative analysis of accented speech, and extend current studies in L2 speech learning theory to large scale. Practically, this study further shows that the computational model proposed in this study can benefit automatic accentedness evaluation system by adding features related to speakers' L1s.Dissertation/ThesisDoctoral Dissertation Speech and Hearing Science 201