An Algorithm For Building Language Superfamilies Using Swadesh Lists

The main contributions of this thesis are the following: i. Developing an algorithm to generate language families and superfamilies given for each input language a Swadesh list represented using the international phonetic alphabet (IPA) notation. ii. The algorithm is novel in using the Levenshtein distance metric on the IPA representation and in the way it measures overall distance between pairs of Swadesh lists. iii. Building a Swadesh list for the author\u27s native Kinyarwanda language because a Swadesh list could not be found even after an extensive search for it. Adviser: Peter Reves

Energy-Efficient Algorithms

We initiate the systematic study of the energy complexity of algorithms (in addition to time and space complexity) based on Landauer's Principle in physics, which gives a lower bound on the amount of energy a system must dissipate if it destroys information. We propose energy-aware variations of three standard models of computation: circuit RAM, word RAM, and transdichotomous RAM. On top of these models, we build familiar high-level primitives such as control logic, memory allocation, and garbage collection with zero energy complexity and only constant-factor overheads in space and time complexity, enabling simple expression of energy-efficient algorithms. We analyze several classic algorithms in our models and develop low-energy variations: comparison sort, insertion sort, counting sort, breadth-first search, Bellman-Ford, Floyd-Warshall, matrix all-pairs shortest paths, AVL trees, binary heaps, and dynamic arrays. We explore the time/space/energy trade-off and develop several general techniques for analyzing algorithms and reducing their energy complexity. These results lay a theoretical foundation for a new field of semi-reversible computing and provide a new framework for the investigation of algorithms.Comment: 40 pages, 8 pdf figures, full version of work published in ITCS 201

Perception of Fa by non-native listeners in a study abroad context

The present study aims at exploring the under-investigated interface between SA and L2 phonological development by assessing the impact of a 3-month SA programme on the pronunciation of a group of 23 Catalan/Spanish learners of English (NNSs) by means of phonetic measures and perceived FA measures. 6 native speakers (NS) in an exchange programme in Spain provided baseline data for comparison purposes. The participants were recorded performing a reading aloud task before (pre-test) and immediately after (post-test) the SA. Another group of 37 proficient non-native listeners, also bilingual in Catalan/Spanish and trained in English phonetics, assessed the NNS' speech samples for degree of FA. Phonetic measures consisted of pronunciation accuracy scores computed by counting pronunciation errors (phonemic deletions, insertions and substitutions, and stress misplacement). Measures of perceived FA were obtained with two experiments. In experiment 1, the listeners heard a random presentation of the sentences produced by the NSs and by the NNSs at pre-test and post-test and rated them on a 7-point Likert scale for degree of FA (1 = “native” , 7 = “heavy foreign accent”). In experiment 2, they heard paired pre-test/post-test sentences (i.e. produced by the same NNS at pre-test and posttest) and indicated which of the two sounded more native-like. Then, they stated their judgment confidence level on a 7-point scale (1 = “unsure”, 7 = “sure”). Results indicated a slight, non-significant improvement in perceived FA after SA. However, a significant decrease was found in pronunciation accuracy scores after SA. Measures of pronunciation accuracy and FA ratings were also found to be strongly correlated. These findings are discussed in light of the often reported mixed results as regards pronunciation improvement during short-term immersion

CloudTree: A Library to Extend Cloud Services for Trees

In this work, we propose a library that enables on a cloud the creation and management of tree data structures from a cloud client. As a proof of concept, we implement a new cloud service CloudTree. With CloudTree, users are able to organize big data into tree data structures of their choice that are physically stored in a cloud. We use caching, prefetching, and aggregation techniques in the design and implementation of CloudTree to enhance performance. We have implemented the services of Binary Search Trees (BST) and Prefix Trees as current members in CloudTree and have benchmarked their performance using the Amazon Cloud. The idea and techniques in the design and implementation of a BST and prefix tree is generic and thus can also be used for other types of trees such as B-tree, and other link-based data structures such as linked lists and graphs. Preliminary experimental results show that CloudTree is useful and efficient for various big data applications

An Algorithm For Building Language Superfamilies Using Swadesh Lists

The main contributions of this thesis are the following: i. Developing an algorithm to generate language families and superfamilies given for each input language a Swadesh list represented using the international phonetic alphabet (IPA) notation. ii. The algorithm is novel in using the Levenshtein distance metric on the IPA representation and in the way it measures overall distance between pairs of Swadesh lists. iii. Building a Swadesh list for the author\u27s native Kinyarwanda language because a Swadesh list could not be found even after an extensive search for it. Adviser: Peter Reves