introduction to dialectometry ii
play

Introduction to Dialectometry II Wilbert Heeringa German Academic - PowerPoint PPT Presentation

Dec 22, 2023 •221 likes •898 views

Introduction to Dialectometry II Wilbert Heeringa German Academic Exchange Service DAAD University of Bielefeld, Faculty of Linguistics and Literary Studies Frisian Academy Abidjan, December, 1923, 2016 1 Topics Validation of distance

  1. Introduction to Dialectometry II Wilbert Heeringa German Academic Exchange Service – DAAD University of Bielefeld, Faculty of Linguistics and Literary Studies Frisian Academy Abidjan, December, 19–23, 2016 1

  2. Topics Validation of distance measures Consistency of distance measures Quality of classifications Cluster algorithms Fuzzy clustering Cophenetic multidimensional scaling maps Reference point maps 2

  3. Validation of distance measures 3

  4. Experiment • In Norway: everybody speaks dialect, there is not a standard language. • In the period 1999–2002 Jørn Almberg and Kristian Skarbø recorded about 50 Norwegian dialects. • The fable ‘The North Wind and the Sun’ was taken as a basis. • This text was also used in IPA handbooks published in 1949 and 1999. • Speakers were asked to translate the text and to read it aloud. • Audio files and transcriptions available at: http://www.ling.hf.ntnu.no/nos/ 4

  5. Experiment • Perception experiment carried out in the Spring of 2000 by Charlotte Gooskens. • 15 recordings of 15 dialects were used. • In each of the 15 locations, a group of 16 to 27 high school pupils listened to all 15 texts. • The texts were presented in a randomized order. 5

  6. Bodø Verdal Bjugn Stjørdal Fræna Trondheim Herøy Lesja The geographic distribution of Lillehammer the 15 Norwegian dialects. Bergen Bø Borre Halden Larvik Time 6

  7. Experiment • Task: each pupil notes for each text the distance of the corresponding dialect compared to his own dialect. • Scale from 1 (similar to own dialect) to 10 (not similar to own dialect). • Final result: a 15 × 15 perceptual distance matrix. 7

  8. Experiment Be Bj Bo Bø Bo Fr Ha He La Le Li St Ti Tr Ve Bergen 1.7 9.0 8.2 8.0 7.7 7.7 8.2 6.9 8.0 8.9 8.5 8.4 4.8 8.5 8.0 " Bjugn 9.1 3.4 6.4 8.2 9.2 5.8 8.3 8.0 8.4 7.3 9.1 2.2 8.0 3.3 2.8 " Bodø 8.7 7.9 1.5 8.3 8.3 6.6 7.9 7.8 7.3 8.0 8.7 6.6 8.1 6.2 6.3 " Bø 8.1 7.8 7.5 1.0 7.7 8.1 4.9 7.8 5.3 6.0 5.1 7.1 6.3 8.2 8.6 " Borre 6.1 8.8 7.8 6.5 1.7 8.5 1.8 7.5 1.6 7.5 2.0 7.2 7.5 8.5 9.1 " Fræna 9.0 7.5 7.1 8.4 8.8 3.1 8.1 7.8 8.5 7.2 9.0 6.6 7.4 6.1 7.6 " Halden 7.0 8.2 8.0 6.8 4.0 8.1 2.8 7.9 2.8 6.6 3.0 7.4 7.0 8.0 8.3 " Herøy 8.6 9.3 8.4 8.5 9.1 7.0 8.6 1.2 9.3 9.3 9.4 8.5 7.5 7.5 8.2 " Larvik 7.4 8.7 7.6 4.0 4.0 7.7 3.2 5.6 3.4 7.1 4.6 8.2 6.8 8.3 7.5 " Lesja 8.5 7.6 7.8 7.4 8.2 7.3 7.6 7.7 7.6 1.0 7.1 6.9 7.2 7.7 8.2 " Lillehammer 6.7 8.3 8.1 6.2 4.4 8.0 3.1 7.5 4.1 7.3 2.7 7.6 6.8 8.7 8.1 " Stjørdal 8.7 3.7 6.8 7.7 8.1 6.0 7.5 7.7 8.3 7.1 8.3 2.0 7.7 3.8 3.4 " Time 7.0 9.3 8.4 8.1 8.4 8.3 8.0 7.2 8.2 9.1 8.8 8.8 1.8 8.8 9.0 " Trondheim 7.8 5.8 6.7 7.5 6.4 7.3 6.0 7.1 5.9 7.9 6.3 4.4 7.6 3.3 6.8 " Verdal 8.8 3.4 6.4 8.2 8.4 5.7 7.2 7.9 7.9 7.4 8.4 1.8 7.9 3.1 2.6 " Perceptual distances among 15 Norwegian dialeact varieties. Row names represent listener groups, column names represent dialect speakers. 8

  9. Average perceptual distances between 15 Norwegian dialects. Darker lines connect closer points, lighter lines more remote ones. Distance pairs A – B / B – A are averaged. 9

  10. Experiment • Using the transcriptions we measure lexical distances and pronunciation distances among the 15 local dialect variaties. • Each dialect text usually consists of 58 different words. • Validation: How well do the dialectometric distances correlate with the perceptual distances? 10

  11. Correlations (1) lexical r expl. var. relative difference value 0.27 7% weighted difference value 0.37 14% pronunciation aggregate r expl. var. Levenshtein (1) 0.71 50% Levenshtein (2) 0.70 49% Levenshtein (3) 0.67 45% Levenshtein PMI (1) 0.71 50% Levenshtein PMI (3) 0.67 45% 11

  12. Correlations (2) • In the measurements binary weighting is used. Suprasegmentals and diacritics are ignored. • No difference between ‘classic’ Levenshtein and PMI Levenshtein, but alignments made by PMI Levenshtein are better, see Wieling, Proki´ c and Nerbonne (2009). 12

  13. Left: perceptual distances. Right: lexical weighted difference value distances. Darker lines connect closer points, lighter lines more remote ones. r = 0 . 37 13

  14. Left: perceptual distances. Right: non-normalized Levenshtein distances. Darker lines connect closer points, lighter lines more remote ones. r = 0 . 71 . 14

  15. Consistency of distance measures 15

  16. Consistency • How many items do we need for dialect comparison? Rule of thumb: 100 items (Goebl). • In order to answer this question more precisely, measure the degree to which different words in the data set give the same signal of linguistic relationships between the dialects: measure Cronbach’s Alpha . • Example: measure Levenshtein distance between three dialects using four words. In this example we normalize Levenshtein distances per word pair. 16

  17. Grouw Haarlem Almelo Levenshtein distances between pronunciations of the word seen . 17

  18. Grouw Haarlem Almelo Levenshtein distances between pronunciations of the word hart . 18

  19. Grouw Haarlem Almelo Levenshtein distances between pronunciations of the word son . 19

  20. Grouw Haarlem Almelo Levenshtein distances between pronunciations of the word house . 20

  21. Consistency • General pattern: Haarlem and Almelo are linguistically relatively close to each other and relatively distant to Grouw. • Levenshtein distances between the three local dialects: seen hart son house Grouw vs. Haarlem 71 25 100 75 Grouw vs. Almelo 83 25 75 33 Haarlem vs. Almelo 60 20 50 50 • Using the values in the columns the words are correlated to each other. 21

  22. Consistency • Correlations between words: r n seen vs. hart 0.85 3 seen vs. son 0.48 3 seen vs. house -0.43 3 hart vs. son 0.87 3 hart vs. house 0.11 3 son vs. house 0.59 3 • The average inter-correlation r is 0.41. 22

  23. Consistency • Cronbach’s α can be written as a function of the number of words and the average inter-correlation among the words: n w × ¯ r α = 1 + ( n w − 1) × ¯ r where n w is the number of words which is in our example 4. • Calculation: 4 × 0 . 41 α = 1 + (4 − 1) × 0 . 41 = 0 . 74 • If all words have the same geographic distribution of variants the value of Cronbach’s alpha is 1, if there is no consistency between the words in the data set the value is 0. • A generally accepted threshold for consistency of the data is 0.70. 23

  24. Consistency • In general: the more items are included, the higher Cronbach’s Alpha. • If the Cronbach’s Alpha value is very low, add more items! 24

  25. Consistency 1.0 0.7 0.8 Cronbachs’s alpha Cronbach’s alpha 0.5 0.6 0.3 0.4 0.2 0.1 0.0 -0.1 0 20 40 60 80 100 0 20 40 60 80 100 120 number of words number of words Left: Cronbach’s α values for random subsets of 2 through 107 words (lexical weighted difference values) and 360 local dialects. From 86 words on α is always higher than 0.70. For 107 words α is equal to 0.75. Right: Cronbach’s α values for random subsets of 2 through 125 words (Levenshtein distance) and 360 local dialects. From 13 words on α is always higher than 0.70. For 125 words α is equal to 0.97. 25

  26. Quality of classifications 26

  27. Quality of classifications • For clustering compare cophenetic distances to original distances. • For multidimensional scaling compare interpoint multidimensional scaling distances to original distances. 27

  28. Cophenetic distances • In a dendrogram the distances between clusters are represented by the length of the branches. Grouw Delft Haarlem Hattem Lochem 0 10 20 30 40 • Cophenetic distance: distance between two local dialects as found in the dendrogram. • Find the shortest path between two local dialects and the longest distance in one direction within the shortest path. 28

  29. Cophenetic distances Grouw Haarlem Delft Hattem Lochem Grouw 0 44 44 44 44 Haarlem 44 0 16 36.25 36.25 Delft 44 16 0 36.25 36.25 Hattem 44 36.25 36.25 0 20 Lochem 44 36.25 36.25 20 0 29

  30. Cophenetic distances • Cophenetic correlation coefficient: measure of how faithfully the pairwise distances between local dialects as suggested by the dendrogram preserve the original pairwise distances. • Correlate the pairwise cophenetic distances with the original pairwise distances: r = 0.99 • The amount of variance in the original distances explained by the cophenetic distances is r 2 × 100 = 97.6%. 30

  31. Interpoint multidimensional scaling distances • With multidimensional scaling the five local dialects are plotted in two-dimensional space so that the distances are preserved as well as possible: 30 Grouw 20 second dimension 10 Lochem Hattem 0 -10 Haarlem Delft -20 -30 -40 -20 0 20 40 fi rst dimension 31

  32. Interpoint multidimensional scaling distances • We can calculate interpoint distances between the local dialects: 30 Grouw 20 second dimension 10 Lochem Hattem 0 -10 Haarlem Delft -20 -30 -40 -20 0 20 40 fi rst dimension • Distance between Grouw (-24,21) and Hattem (18, 6): � ( − 24 − 18) 2 + (21 − 6) 2 = 44 . 6 32

Recommend

Reverse dialectometry Geography as a probe into linguistic theory Jeroen van Craenenbroeck KU

Reverse dialectometry Geography as a probe into linguistic theory Jeroen van Craenenbroeck KU

Introduction Dialectometry Reverse dialectometry Conclusion References Reverse dialectometry Geography as a probe into linguistic theory Jeroen van Craenenbroeck KU Leuven/CRISSP Maps and Grammar September 1718, 2014 Introduction

1.48k views • 118 slides
Introduction to Dialectometry Wilbert Heeringa Spr akbanken, University of Gothenburg 30

Introduction to Dialectometry Wilbert Heeringa Spr akbanken, University of Gothenburg 30

Introduction to Dialectometry Wilbert Heeringa Spr akbanken, University of Gothenburg 30 january 2019 1 Introduction 2 What is dialectometry? The measure of dialect (Jean S eguy). Measures the degree of difference or

1.4k views • 65 slides
Introduction to Dialectometry III Wilbert Heeringa German Academic Exchange Service DAAD

Introduction to Dialectometry III Wilbert Heeringa German Academic Exchange Service DAAD

Introduction to Dialectometry III Wilbert Heeringa German Academic Exchange Service DAAD University of Bielefeld, Faculty of Linguistics and Literary Studies Frisian Academy Abidjan, December, 1923, 2016 1 Topics Gabmap Literature 2

902 views • 50 slides
INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION

INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION

TRAINING COURSE ON SOCIAL PROTECTION & FORMALIZATION TRINIDAD AND TOBAGO MARCH 15, 2017 INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION INTRODUCTION Design of the NIS Assistance from the

547 views • 23 slides
INTRODUCTION Introduction 2/42 INTRODUCTION Alternations I am giving bread to the

INTRODUCTION Introduction 2/42 INTRODUCTION Alternations I am giving bread to the

Patterns of variation in the expression of case and agreement Andrs Brny Leiden University Centre for Linguistics 9 November 2019, BaSIS Workshop a.barany@hum.leidenuniv.nl INTRODUCTION Introduction 2/42 INTRODUCTION

1.37k views • 42 slides
Introduction Introduction Introduction Introduction Outline Motivation Failures

Introduction Introduction Introduction Introduction Outline Motivation Failures

Introduction Introduction Introduction Introduction Outline Motivation Failures Definition and concepts Process and product properties Principles SE Approaches Motivation Software and the economy The economies of

1.03k views • 49 slides
Introduction Introduction Introduction Nationwide Cause for Concern 1

Introduction Introduction Introduction Nationwide Cause for Concern 1

Introduction Introduction Introduction Nationwide Cause for Concern 1 https://www.cdc.gov/std/stats17/infographic.htm Introduction Epidemiology in Western Colorado CPHE Surveillance Data Report, May 2018 Chlamydia Epidemiology in Western

977 views • 39 slides
DAQ introduction Purpose of this talk : (1) Introduction for those who have not been in every

DAQ introduction Purpose of this talk : (1) Introduction for those who have not been in every

DAQ introduction Purpose of this talk : (1) Introduction for those who have not been in every meeting (2) Some ideas of diagrams for section 7.1 (Introduction) of TP. Giles Barr 25 Jan 2018, Pembroke College On DUNE, the reality is there is a

474 views • 10 slides
INTRODUCTION cf. Schneider, Chapter 1 INTRODUCTION THEY ARE OUT TO GET YOU INTRODUCTION WHAT

INTRODUCTION cf. Schneider, Chapter 1 INTRODUCTION THEY ARE OUT TO GET YOU INTRODUCTION WHAT

ADVANCED COMPUTER SECURITY INTRODUCTION cf. Schneider, Chapter 1 INTRODUCTION THEY ARE OUT TO GET YOU INTRODUCTION WHAT IS SECURITY? A systems security policies describe What the system is supposed to do Store and provide access

479 views • 16 slides
Overview Introduction to SMIL Introduction to W3C and XML Introduction to SMIL

Overview Introduction to SMIL Introduction to W3C and XML Introduction to SMIL

Overview Introduction to SMIL Introduction to W3C and XML Introduction to SMIL Writing a SMIL file Adding Media Objects Martin Halvey Clipping media files January 2008 Timing and Synchronising Layout World Wide

387 views • 14 slides
14 Introduction Introduction Bad guys can put malware into Example: hosts

14 Introduction Introduction Bad guys can put malware into Example: hosts

Introduction Introduction source Encapsulation ISO/OSI reference model message M application segment H t H t M transport network datagram H n H n H t M presentation: allow applications to frame link H l H n H t M interpret

583 views • 4 slides
Previous Lecture Introduction to SMIL 2 Introduction to W3C and XML Introduction to SMIL

Previous Lecture Introduction to SMIL 2 Introduction to W3C and XML Introduction to SMIL

Previous Lecture Introduction to SMIL 2 Introduction to W3C and XML Introduction to SMIL Writing a SMIL file Adding Media Objects Martin Halvey Clipping media files January 2008 Timing and Synchronising Layout

322 views • 8 slides
Lecture 1 Andreas Habegger Introduction Zynq Introduction Zynq Introduction Zynq PS vs. PL

Lecture 1 Andreas Habegger Introduction Zynq Introduction Zynq Introduction Zynq PS vs. PL

Introduction Zynq Lecture 1 Andreas Habegger Introduction Zynq Introduction Zynq Introduction Zynq PS vs. PL Processing System Processor Peripherals Data Buses AXI Bus Conclusion BTE5380 - Embedded Systems Octobre 2014 Andreas Habegger

1.81k views • 30 slides
2018.06 01 SMILE5 Introduction S E 5 02 Alpha Cloud M I L 03 Company Introduction 04

2018.06 01 SMILE5 Introduction S E 5 02 Alpha Cloud M I L 03 Company Introduction 04

2018.06 01 SMILE5 Introduction S E 5 02 Alpha Cloud M I L 03 Company Introduction 04 Project References S E 5 PART.1 SMILE5 Introduction M I L Introduction STORION-SMILE5 Residential Energy Storage System Inverter 5kW Output Input

1.06k views • 25 slides
Introduction to CICS Course introduction Course introduction What is CICS? What is an

Introduction to CICS Course introduction Course introduction What is CICS? What is an

Introduction to CICS Course introduction Course introduction What is CICS? What is an application server? Why use an application server? Course introduction Services provided by CICS How CICS applications are defined Scaling CICS to meet

1.84k views • 146 slides
Network Visualization Introduction Presented by Shahed Introduction Introduction Basic

Network Visualization Introduction Presented by Shahed Introduction Introduction Basic

Network Visualization Introduction Presented by Shahed Introduction Introduction Basic building blocks Node Links (relationship between nodes) Spatial information Network data

584 views • 9 slides
Introduction Introduction (1) Main argument of the paper: universities are not only

Introduction Introduction (1) Main argument of the paper: universities are not only

Le jugement des pairs comme outil de management des universits Peer-review as a management tool Christine Musselin (CSO, Sciences Po et CNRS) Avril 2013, Lirrsistible ascension du capitalisme acadmique Introduction Introduction (1)

590 views • 28 slides
JABLOTRON JA-100 introduction November 2011 Introduction Todays goals First introduction of

JABLOTRON JA-100 introduction November 2011 Introduction Todays goals First introduction of

JABLOTRON JA-100 introduction November 2011 Introduction Todays goals First introduction of the brand new JA-100 alarm system Visions Basic architecture System components Setting Help us with final validations You are the FIRST ones

1.69k views • 111 slides
Introduction Introduction to storage and to storage and filesystems filesystems Introduction

Introduction Introduction to storage and to storage and filesystems filesystems Introduction

Moreno Baricevic Gilberto Daz Axel Kohlmeyer Stefano Cozzini ULA ICTP CNR-IOM DEMOCRITOS Merida, VENEZUELA Trieste, ITALY Trieste, ITALY Introduction Introduction to storage and to storage and filesystems filesystems Introduction

1.19k views • 51 slides
1 Introduction Introduction Communication System Baseband an adjective that describes

1 Introduction Introduction Communication System Baseband an adjective that describes

Introduction Introduction Physical Layer Mobile network Global ISP Provides the means to transmit bits Basic Concepts of from sender to receiver, Data Transmission Defines the mechanical, electrical, and Home network timing

463 views • 7 slides
Welcome! Todays Agenda: Topic Introduction Course Introduction Team Practical

Welcome! Todays Agenda: Topic Introduction Course Introduction Team Practical

INFOGR Computer Graphics Jacco Bikker - April-July 2015 - Lecture 1: Introduction Welcome! Todays Agenda: Topic Introduction Course Introduction Team Practical Details Assignments Field Study State of

869 views • 62 slides
Introduction (00) RNDr. Martin Madaras, PhD. madaras@skeletex.xyz Introduction Introduction

Introduction (00) RNDr. Martin Madaras, PhD. madaras@skeletex.xyz Introduction Introduction

Virtual and Augmented Reality Introduction (00) RNDr. Martin Madaras, PhD. madaras@skeletex.xyz Introduction Introduction Who am I? What do I do here? 2 About me Short research bio: - 2014 - finished PhD at FMFI UK - 2014 2016 -

1.3k views • 39 slides
PRESENTATION The Introduction What is the Introduction ? The introduction prepares the audience

PRESENTATION The Introduction What is the Introduction ? The introduction prepares the audience

PRESENTATION The Introduction What is the Introduction ? The introduction prepares the audience for your presentation. It tells them what your presentation is about, why it is important, and finally, what to listen for in your speech. Get the

505 views • 3 slides
How to make a presentation with L A T EX? Introduction to L A T EX Introduction to Beamer

How to make a presentation with L A T EX? Introduction to L A T EX Introduction to Beamer

Introduction to Beamer Hafida Benhidour How to make a presentation with L A T EX? Introduction to L A T EX Introduction to Beamer Introduction to Beamer Hafida Benhidour Department of computer science King Saud University November

732 views • 49 slides

More recommend