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Rnn Classification Of English Vowels: Nasalized Or Not, Ling Liu, Mans Hulden, Rebecca Scarborough 2019 University of Colorado Boulder

Rnn Classification Of English Vowels: Nasalized Or Not, Ling Liu, Mans Hulden, Rebecca Scarborough

Proceedings of the Society for Computation in Linguistics

Vowel nasality is perceived and used by English listeners though it is not phonemic. Feature-based classifiers have been built to evaluate what features are useful for nasality perception and measurement. These classifiers require heavy high-level feature engineering with most features discrete and measured at discrete points. Recurrent neural networks can take advantage of sequential information, and has the advantage of freeing us from high-level feature engineering and potentially being stronger simulation models with a holistic view. Therefore, we constructed two types of RNN classifiers (vanilla RNN and LSTM) with MFCCs of the vowel as input to predict whether the vowel ...


Developing A Real-Time Translator From Neural Signals To Text: An Articulatory Phonetics Approach, Lindy Comstock, Ariel Tankus, Michelle Tran, Nader Pouratian, Itzhak Fried, William Speier 2019 University of California, Los Angeles

Developing A Real-Time Translator From Neural Signals To Text: An Articulatory Phonetics Approach, Lindy Comstock, Ariel Tankus, Michelle Tran, Nader Pouratian, Itzhak Fried, William Speier

Proceedings of the Society for Computation in Linguistics

New developments in brain-computer interfaces (BCI) harness machine learning to decode spoken language from electrocorticographic (ECoG) and local field potential (LFP) signals. Orienting to signals associated with motor movements that produce articulatory features improves phoneme detection quality: individual phonemes share features, but possess a unique feature set; classification by feature set allows for a finer distinction between neural signals. Data indicates vowels are more detectable, consonants have greater detection accuracy, place of articulation informs precision, and manner of articulation affects recall. Findings have implications for the multisensory integration of speech and the role of motor imagery in phonemic neural representations.


On The Interaction Between Dependency Frequency And Semantic Fit In Sentence Processing, Soo Hyun Ryu, Rui P. Chaves 2019 University at Buffalo

On The Interaction Between Dependency Frequency And Semantic Fit In Sentence Processing, Soo Hyun Ryu, Rui P. Chaves

Proceedings of the Society for Computation in Linguistics

No abstract provided.


Non-Entailed Subsequences As A Challenge For Natural Language Inference, Richard T. McCoy, Tal Linzen 2019 Johns Hopkins University

Non-Entailed Subsequences As A Challenge For Natural Language Inference, Richard T. Mccoy, Tal Linzen

Proceedings of the Society for Computation in Linguistics

No abstract provided.


Recursive Neural Networks For Semantic Sentence Representation, Liam S. Geron 2018 The Graduate Center, City University of New York

Recursive Neural Networks For Semantic Sentence Representation, Liam S. Geron

All Dissertations, Theses, and Capstone Projects

Semantic representation has a rich history rife with both complex linguistic theory and computational models. Though this history stretches back almost 50 years (Salton, 1971), recently the field has undergone an unexpected shift in paradigm thanks to the work of Mikolov et al., 2013(a & b) which has proven that vector-space semantic models can capture large amounts of semantic information. As of yet, these semantic representations are computed at the word level, and finding a semantic representation of a phrase is a much more difficult challenge. Mikolov et al., 2013(a&b) proved that their word vectors can be composed ...


Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson 2018 Tsinghua University, China

Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson

Electrical and Computer Engineering Faculty Publications

Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers ...


Perception & Perspective: An Analysis Of Discourse And Situational Factors In Reference Frame Selection, Robert Ross, Kavita E. Thomas 2018 Dublin Institute of Technology

Perception & Perspective: An Analysis Of Discourse And Situational Factors In Reference Frame Selection, Robert Ross, Kavita E. Thomas

Conference papers

To integrate perception into dialogue, it is necessary to bind spatial language descriptions to reference frame use. To this end, we present an analysis of discourse and situational factors that may influence reference frame choice in dialogues. We show that factors including spatial orientation, task, self and other alignment, and dyad have an influence on reference frame use. We further show that a computational model to estimate reference frame based on these features provides results greater than both random and greedy reference frame selection strategies.


Describing Doggo-Speak: Features Of Doggo Meme Language, Jennifer Bivens 2018 The Graduate Center, City University of New York

Describing Doggo-Speak: Features Of Doggo Meme Language, Jennifer Bivens

All Dissertations, Theses, and Capstone Projects

Doggo-speak is a specialized way of writing most commonly associated with captions on Doggo memes, humorous images of dogs shared in online communities. This paper will explore linguistic features of Doggo-speak through analysis of social media posts by Doggo fan pages. It will use the discussed features as inputs to five machine learning classifiers and will show, through this classification task, that the discussed features are sufficient for distinguishing between Doggo-speak and more general English text.


Multimodal Depression Detection: An Investigation Of Features And Fusion Techniques For Automated Systems, Michelle Renee Morales 2018 The Graduate Center, City University of New York

Multimodal Depression Detection: An Investigation Of Features And Fusion Techniques For Automated Systems, Michelle Renee Morales

All Dissertations, Theses, and Capstone Projects

Depression is a serious illness that affects a large portion of the world’s population. Given the large effect it has on society, it is evident that depression is a serious health issue. This thesis evaluates, at length, how technology may aid in assessing depression. We present an in-depth investigation of features and fusion techniques for depression detection systems. We also present OpenMM: a novel tool for multimodal feature extraction. Lastly, we present novel techniques for multimodal fusion. The contributions of this work add considerably to our knowledge of depression detection systems and have the potential to improve future systems ...


Speech Perception In “Bubble” Noise: Korean Fricatives And Affricates By Native And Non-Native Korean Listeners, Jiyoung Choi 2018 The Graduate Center, City University of New York

Speech Perception In “Bubble” Noise: Korean Fricatives And Affricates By Native And Non-Native Korean Listeners, Jiyoung Choi

All Dissertations, Theses, and Capstone Projects

The current study examines acoustic cues used by second language learners of Korean to discriminate between Korean fricatives and affricates in noise and how these cues relate to those used by native Korean listeners. Stimuli consist of naturally-spoken consonant-vowel-consonant-vowel (CVCV) syllables: /sɑdɑ/, /s*ɑdɑ/, /tʃɑdɑ/, /tʃhɑdɑ/, and /tʃ*ɑdɑ/. In this experiment, the “bubble noise” methodology of Mandel at al. (2016) was used to identify the time-frequency locations of important cues in each utterance, i.e., where audibility of the location is significantly correlated with correct identification of the utterance in noise. Results show that non-native Korean listeners ...


Intergroup Variability In Personality Recognition, Arundhati Sengupta 2018 The Graduate Center, City University of New York

Intergroup Variability In Personality Recognition, Arundhati Sengupta

All Dissertations, Theses, and Capstone Projects

Automatic Identification of personality in conversational speech has many applications in natural language processing such as leader identification in a meeting, adaptive dialogue systems, and dating websites. However, the widespread acceptance of automatic personality recognition through lexical and vocal characteristics is limited by the variability of error rate in a general purpose model among speakers from different demographic groups. While other work reports accuracy, we explored error rates of automatic personality recognition task using classification models for different genders and native language groups (L1). We also present a statistical experiment showing the influence of gender and L1 on the relation ...


Automatic Analysis Of Musical Lyrics, Joanna Gormley 2018 Merrimack College

Automatic Analysis Of Musical Lyrics, Joanna Gormley

Honors Senior Capstone Projects

Is music getting less sophisticated over time? That is the question which this study aims to answer, with the goal of improving upon previous analysis done on the topic. The blog posts which inspired this project lacked accuracy and dimensionality. Realizing that a larger data set of songs would make a significant difference in the precision of our analysis, we set out to design a piece of software constructed with the capability to analyze several thousand songs. Mimicking previous works which analyzed sophistication of music, the software focuses on the lyrics of songs. Three metrics were used in order to ...


Role Of Information Technology In Development Of Eritrean Language - ኣበርክቶ ቴክኖሎጂ ሓበሬታ ኣብ ምምዕባል ቋንቋታት ኤርትራ, Filmon Gebreyesus Ph.D 2018 Santa Clara University

Role Of Information Technology In Development Of Eritrean Language - ኣበርክቶ ቴክኖሎጂ ሓበሬታ ኣብ ምምዕባል ቋንቋታት ኤርትራ, Filmon Gebreyesus Ph.D

Symposium on Eritrean Literature

Information technology has been affecting us in every day of our lives, especially social media has been the main means of communication in our society. But, all the access to this current and ever-growing technology has always been limited to using it in English, Arab or other languages because our language didn’t come up to speed with the current technology.

Though there has been lots of efforts to develop Tigrigna or other languages application programs to help us use our language, there are still lots of gaps that could be filled to achieve the competence of our languages. In ...


Innovative Implementation Of A Web-Based Rating System For Individualizing Online English Speaking Instruction, Hyejin Yang, Elena Cotos 2018 Sookmyung Women’s University

Innovative Implementation Of A Web-Based Rating System For Individualizing Online English Speaking Instruction, Hyejin Yang, Elena Cotos

English Publications

The primary goal of computer-assisted language learning (CALL) in general, and of online language instruction in particular, is to create and evaluate language learning opportunities. To be effective, online language courses need to be guided by an integrated set of theoretical perspectives to second language acquisition (SLA), as well as by specific curricular goals, learning objectives and outcomes, appropriate tasks and necessary materials, and learners’ characteristics and abilities – to name a few factors that are essential in both online and face-to-face teaching (Xu & Morris, 2007). Doughty and Long (2003) articulate pedagogical principles for computer-enhanced language teaching, which highlight the importance ...


Does The Test Work? Evaluating A Web-Based Language Placement Test, Avizia Long, Sun-Young Shin, Kimberly Geeslin, Erik Willis 2018 Texas Tech University

Does The Test Work? Evaluating A Web-Based Language Placement Test, Avizia Long, Sun-Young Shin, Kimberly Geeslin, Erik Willis

Faculty Publications

In response to the need for examples of test validation from which everyday language programs can benefit, this paper reports on a study that used Bachman’s (2005) assessment use argument (AUA) framework to examine evidence to support claims made about the intended interpretations and uses of scores based on a new web-based Spanish language placement test. The test, which consisted of 100 items distributed across five item types (sound discrimination, grammar, listening comprehension, reading comprehension, and vocabulary), was tested with 2,201 incoming first-year and transfer students at a large, Midwestern public university. Analyses of internal consistency and validity ...


Modeling The Decline In English Passivization, Liwen Hou, David Smith 2018 Northeastern University

Modeling The Decline In English Passivization, Liwen Hou, David Smith

Proceedings of the Society for Computation in Linguistics

Evidence from the Hansard corpus shows that the passive voice in British English has declined in relative frequency over the last two centuries. We investigate which factors are predictive of whether transitive verb phrases are passivized. We show the increasing importance of the person-hierarchy effects observed by Bresnan et al. (2001), with increasing strength of the constraint against passivizing clauses with local agents, as well as the rising prevalence of such agents. Moreover, our ablation experiments on the Wall Street Journal and Hansard corpora provide support for the unmarked information structure of ‘given’ before ‘new’ noted by Halliday (1967).


Quantifying The Trade-Off Between Two Types Of Morphological Complexity, Ryan Cotterell, Christo Kirov, Mans Hulden, Jason Eisner 2018 Johns Hopkins University

Quantifying The Trade-Off Between Two Types Of Morphological Complexity, Ryan Cotterell, Christo Kirov, Mans Hulden, Jason Eisner

Proceedings of the Society for Computation in Linguistics

No abstract provided.


T-Orders Across Categorical And Probabilistic Constraint-Based Phonology, Arto Tapani Anttila, Giorgio Magri 2018 Stanford University

T-Orders Across Categorical And Probabilistic Constraint-Based Phonology, Arto Tapani Anttila, Giorgio Magri

Proceedings of the Society for Computation in Linguistics

No abstract provided.


Distributed Morphology As A Regular Relation, Marina Ermolaeva, Daniel Edmiston 2018 University of Chicago

Distributed Morphology As A Regular Relation, Marina Ermolaeva, Daniel Edmiston

Proceedings of the Society for Computation in Linguistics

This research reorganizes the Distributed Morphology (DM) framework to work over strings. Typically, DM operates on binary trees, with the syntax-morphology interface implicitly treated as a tree-transducer. We contend that using (binary) trees is overpowered, predicting patterns unattested in natural language. Assuming the standard Y-model, DM operating on trees presumes that the flattening of the derivation for PF takes place post-morphology. We however flatten the structure above the morphological module, between the syntax and morphology. Restricting the morphological component to working on strings, we correctly predict that morphology can be modeled with regular string languages.


Statistical Learning Theory And Linguistic Typology: A Learnability Perspective On Ot’S Strict Domination, Émile Enguehard, Edward Flemming, Giorgio Magri 2018 École Normale Supérieure

Statistical Learning Theory And Linguistic Typology: A Learnability Perspective On Ot’S Strict Domination, Émile Enguehard, Edward Flemming, Giorgio Magri

Proceedings of the Society for Computation in Linguistics

This paper develops a learnability argument for strict domination by looking at the generalization error of learners trained on OT and HG target grammars. The argument is based on both a review of error bounds in the recent statistical learning literature and simulation results on realistic phonological test cases.


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