Evaluation of a Segmental Durations Model for TTS

Size: px
Start display at page:

Download "Evaluation of a Segmental Durations Model for TTS"

Transcription

1 Speech NLP Session Evaluation of a Segmental Durations Model for TTS João Paulo Teixeira, Diamantino Freitas* Instituto Politécnico de Bragança *Faculdade de Engenharia da Universidade do Porto

2 Overview Objectives Labelled Database for European Portuguese FEUP/IPB-DB Pre-processing Syllable division Intonation groups Set of features Model Objective Evaluation Subjective Evaluation Perceptual Test Audio examples Conclusion and future work

3 Objectives Prosody model for FEUPTTS Input features automatically extracted from text FEUP/IPB-DB were used for analysis/training. Extract durations for 44 types of segments of Portuguese set of phonemes: 9 oral vowels - 6 stop consonants nasal semi-vowels - 6 occlusive part of stop cons. semi-vowels - 3 nasal consonants 5 nasal vowels - 5 lateral consonants - 6 fricative consonants

4 Corpus FEUP/IPB-DB Texts were extracted from Portuguese newspapers containing all types of sentences. Read speech from professional male speaker in a regular broadcast studio. Speech ratio of. phonemes/sec. Manually labelled DB in 3 levels: Segments of phonemes and pauses tonic syllable in the word Word boundaries Phrase boundaries (including all punctuation marks) Training set - 6 tracks total of 8 minutes of speech Test set track total of 4 minutes of speech. Example can be found in

5 Relative frequency of segments in FEUP/IPB-DB (%) a 6 E i O o u j w j~ w~6~ e~ i~o~ u~ p!p t!t k!k b!b d!d g!g m n J l l* L r R v f z s S Z

6 Relative frequency of segments (%) Training set Test set a 6 E i O o u j w j~ w~ 6~ e~ i~ o~ u~ p!p t!t k!k b!b d!d g!g m n J l l* L r R v f z s S Z

7 Pre-processing Syllabification Applied to phonemes sequences error =.89% Applied to text error =.6% Intonation groups Simple rules without knowledge of syntax and semantic: Group of words with more than syllables in total. Group never ends with words of less than 3 phonemes. Phrase marks are always group boundaries. Last tonic syllable is the group accent. Example: É a guerra declarada, entre a Distrital socialista de Portalegre, liderada por Ceia da Silva, e a concelhia de Elvas, presidida por Rondão de Almeida.

8 Set of Features Feature - Codification # nodes Segment Identity of Distance to tonic syllable coded in 5 levels Previous segment (-) of Next segment (+) of Next segment (+) of 4 4 Next segment (+3) of Distance to next pause number of segments Position in phrase from beginning and end of phrase Position in group from beginning and end of group Type of vowel length in syllable coded in 5 levels Length of the accent group number of syllables and phonemes Position of accent group in sentence first; other; last. 3 Suppression or non-suppression of last vowel yes/not Type of syllable coded in 9 levels Type of previous syllable coded in 9 levels Type of vowel in previous syllable - coded in 5 levels Type of vowel in next syllable coded in 5 levels Correlation r. to to.3.5 to.8.8 to.4.5 to...4 to.4.3 to.5..3 to.5. to

9 Neural Network Model Architecture p p Σ p 3... Σ Σ Σ b, b, b, Σ b 3, b,3 Σ b, Σ d b,4 p n

10 General Results Equation Training set Test set i d i σ =, d = e e, e = x y N r V = = XY, XY,, VXY, σx. σy δ = i i i i i i N e i ( xi x).( yi y) i N 9,85 ms.834 4,7 ms 9,46 ms.839 4,3 ms

11 Target and Predicted Durations in Test set 5 R =.839 Best Linear Fit: A = (.68) T + (6.9) Data Points Best Linear Fit A = T 5 A T

12 e (ms) Normal Probability Plot Probability e (ms)

13 Histogram of real and predicted durations for vowel [a] 5 a - Durações reais ms a - Durações estimadas ms

14 Perceptual Evaluation 5 Paragraphs Blind test with 3 stimulus of each paragraph (original, model, average), presented in random order. 9 subjects Evaluation of rhythmic characteristics in a scale of 5.

15 Perceptual Test Score's by Subjects and Paragraph Original Model Average Original Model Average Average 3 Average Subjects Paragraph

16 Perceptual Test General Score's 5 Values Real Model Average

17 5 Conhece a situação na pele. Aprendeu-a na idade em que se aprende e se não esquece. Original Duration Predicted Duration 5 Average Duration

18 Audio Examples Conhece a situação na pele. Aprendeu-a na idade em que se aprende e se não esquece. Original Psola Manipulation of predicted durations σ =.8 ms; corr. coef. =.9 Psola Manipulation of average durations σ = 33.4 ms; Mas, que igualdade perante a lei? Que igualdade quando para muitos a justiça é praticamente inacessível? Como podem esses reclamar o cumprimento da lei, sem dinheiro para pagar a bons advogados e os elevados custos de um processo? Original Psola Manipulation of predicted durations σ = 9.8 ms; corr. coef. =.84

19 Conclusions Neural Network model to predict segmental durations. Objective evaluation gives an r =.84 and σ = 9.5 ms. Subjective evaluation gives a score of 4. against 4.3 for original and 3.53 for the average durations. More Linguistic information may possible improve the model. Considering the applicability to TTS systems, differences less than cycle ( ms) are irrelevant in voiced sounds. Major errors happen in very long sounds.

Thirukkural - A Text-to-Speech Synthesis System

Thirukkural - A Text-to-Speech Synthesis System Thirukkural - A Text-to-Speech Synthesis System G. L. Jayavardhana Rama, A. G. Ramakrishnan, M Vijay Venkatesh, R. Murali Shankar Department of Electrical Engg, Indian Institute of Science, Bangalore 560012,

More information

PERCENTAGE ARTICULATION LOSS OF CONSONANTS IN THE ELEMENTARY SCHOOL CLASSROOMS

PERCENTAGE ARTICULATION LOSS OF CONSONANTS IN THE ELEMENTARY SCHOOL CLASSROOMS The 21 st International Congress on Sound and Vibration 13-17 July, 2014, Beijing/China PERCENTAGE ARTICULATION LOSS OF CONSONANTS IN THE ELEMENTARY SCHOOL CLASSROOMS Dan Wang, Nanjie Yan and Jianxin Peng*

More information

Efficient diphone database creation for MBROLA, a multilingual speech synthesiser

Efficient diphone database creation for MBROLA, a multilingual speech synthesiser Efficient diphone database creation for, a multilingual speech synthesiser Institute of Linguistics Adam Mickiewicz University Poznań OWD 2010 Wisła-Kopydło, Poland Why? useful for testing speech models

More information

L2 EXPERIENCE MODULATES LEARNERS USE OF CUES IN THE PERCEPTION OF L3 TONES

L2 EXPERIENCE MODULATES LEARNERS USE OF CUES IN THE PERCEPTION OF L3 TONES L2 EXPERIENCE MODULATES LEARNERS USE OF CUES IN THE PERCEPTION OF L3 TONES Zhen Qin, Allard Jongman Department of Linguistics, University of Kansas, United States qinzhenquentin2@ku.edu, ajongman@ku.edu

More information

Interpreting areading Scaled Scores for Instruction

Interpreting areading Scaled Scores for Instruction Interpreting areading Scaled Scores for Instruction Individual scaled scores do not have natural meaning associated to them. The descriptions below provide information for how each scaled score range should

More information

Functional Auditory Performance Indicators (FAPI)

Functional Auditory Performance Indicators (FAPI) Functional Performance Indicators (FAPI) An Integrated Approach to Skill FAPI Overview The Functional (FAPI) assesses the functional auditory skills of children with hearing loss. It can be used by parents,

More information

VA English Standards of Learning Related to Spelling. Kindergarten

VA English Standards of Learning Related to Spelling. Kindergarten VA English Standards of Learning Related to Spelling Kindergarten K.4 The student will identify, say, segment, and blend various units of speech sounds. a) Begin to discriminate between spoken sentences,

More information

PortuguesePod101.com Learn Portuguese with FREE Podcasts

PortuguesePod101.com Learn Portuguese with FREE Podcasts Introduction First Impressions: Wow Your Portuguese Friends! Portuguese English Vocabulary Phrase Usage 3 Grammar Points 3 Cultural Insight 4 Portuguese Oi. Meu nome é. Oi. Meu nome é. Prazer em conhecê-la.

More information

Regression Analysis: A Complete Example

Regression Analysis: A Complete Example Regression Analysis: A Complete Example This section works out an example that includes all the topics we have discussed so far in this chapter. A complete example of regression analysis. PhotoDisc, Inc./Getty

More information

Prosodic Phrasing: Machine and Human Evaluation

Prosodic Phrasing: Machine and Human Evaluation Prosodic Phrasing: Machine and Human Evaluation M. Céu Viana*, Luís C. Oliveira**, Ana I. Mata***, *CLUL, **INESC-ID/IST, ***FLUL/CLUL Rua Alves Redol 9, 1000 Lisboa, Portugal mcv@clul.ul.pt, lco@inesc-id.pt,

More information

SASSC: A Standard Arabic Single Speaker Corpus

SASSC: A Standard Arabic Single Speaker Corpus SASSC: A Standard Arabic Single Speaker Corpus Ibrahim Almosallam, Atheer AlKhalifa, Mansour Alghamdi, Mohamed Alkanhal, Ashraf Alkhairy The Computer Research Institute King Abdulaziz City for Science

More information

INCREASE YOUR PRODUCTIVITY WITH CELF 4 SOFTWARE! SAMPLE REPORTS. To order, call 1-800-211-8378, or visit our Web site at www.pearsonassess.

INCREASE YOUR PRODUCTIVITY WITH CELF 4 SOFTWARE! SAMPLE REPORTS. To order, call 1-800-211-8378, or visit our Web site at www.pearsonassess. INCREASE YOUR PRODUCTIVITY WITH CELF 4 SOFTWARE! Report Assistant SAMPLE REPORTS To order, call 1-800-211-8378, or visit our Web site at www.pearsonassess.com In Canada, call 1-800-387-7278 In United Kingdom,

More information

An open-source rule-based syllabification tool for Brazilian Portuguese

An open-source rule-based syllabification tool for Brazilian Portuguese Neto et al. Journal of the Brazilian Computer Society (2015) 21:1 DOI 10.1186/s13173-014-0021-9 RESEARCH Open Access An open-source rule-based syllabification tool for Brazilian Portuguese Nelson Neto

More information

RF.1.1. Domain: Foundational Skills. Cluster: Print Concepts

RF.1.1. Domain: Foundational Skills. Cluster: Print Concepts RF.1.1 Domain: Foundational Skills Cluster: Print Concepts Standards: Demonstrate understanding of the organization and basic features of print. (RF.1.1a) Recognize the distinguishing features of a sentence

More information

Reading Assessment Checklist Behaviors to Notice, Teach and Support

Reading Assessment Checklist Behaviors to Notice, Teach and Support Behaviors to Notice Teach Level A/B (Fountas and Pinnell) - DRA 1/2 - NYC ECLAS 2 Solving Words - Locates known word(s) in. Analyzes words from left to right, using knowledge of sound/letter relationships

More information

Child-speak Reading Level 1 APP AF1 AF2 AF3 AF4 AF5 AF6 AF7 Use a range of strategies, including accurate decoding text, to read for meaning

Child-speak Reading Level 1 APP AF1 AF2 AF3 AF4 AF5 AF6 AF7 Use a range of strategies, including accurate decoding text, to read for meaning Child-speak Reading Level 1 APP In some usually I can break down and blend consonant vowel consonant words e.g. cat (1c) I can recognise some familiar words in the I read. (1c) When aloud, I know the sentences

More information

Connecting the dots between

Connecting the dots between Connecting the dots between Research Team: Carla Abreu, Jorge Teixeira, Prof. Eugénio Oliveira Domain: News Research Keywords: Natural Language Processing, Information Extraction, Machine Learning. Objective

More information

Proceedings of Meetings on Acoustics

Proceedings of Meetings on Acoustics Proceedings of Meetings on Acoustics Volume 19, 2013 http://acousticalsociety.org/ ICA 2013 Montreal Montreal, Canada 2-7 June 2013 Speech Communication Session 2aSC: Linking Perception and Production

More information

Acoustic coustic Realization and Perception of English Lexical Stress by Mandarin Learners

Acoustic coustic Realization and Perception of English Lexical Stress by Mandarin Learners Acoustic coustic Realization and Perception of English Lexical Stress by Mandarin Learners Yuwen Lai University of British Columbia University of Kansas Joan Sereno University of Kansas Allard Jongman

More information

CHARTES D'ANGLAIS SOMMAIRE. CHARTE NIVEAU A1 Pages 2-4. CHARTE NIVEAU A2 Pages 5-7. CHARTE NIVEAU B1 Pages 8-10. CHARTE NIVEAU B2 Pages 11-14

CHARTES D'ANGLAIS SOMMAIRE. CHARTE NIVEAU A1 Pages 2-4. CHARTE NIVEAU A2 Pages 5-7. CHARTE NIVEAU B1 Pages 8-10. CHARTE NIVEAU B2 Pages 11-14 CHARTES D'ANGLAIS SOMMAIRE CHARTE NIVEAU A1 Pages 2-4 CHARTE NIVEAU A2 Pages 5-7 CHARTE NIVEAU B1 Pages 8-10 CHARTE NIVEAU B2 Pages 11-14 CHARTE NIVEAU C1 Pages 15-17 MAJ, le 11 juin 2014 A1 Skills-based

More information

Kindergarten. Syllabus Outcomes. Syllabus Content

Kindergarten. Syllabus Outcomes. Syllabus Content Kindergarten Syllabus Outcomes ENe-2A: Compose simple texts to convey and idea or message ENe-4A: Demonstrates developing skills and strategies to read, view and comprehend short, predictable texts on

More information

As Approved by State Board 4/2/09

As Approved by State Board 4/2/09 Improving students' ability to learn, communicate, and collaborate through literacy education As Approved by State Board 4/2/09 Nebraska Language Arts Standards As approved by State Board 4/2/09 Table

More information

Reading Goals by Skills 1 st Grade. Content Standard 9: Comprehension. Content Standard 8: Foundations of Reading

Reading Goals by Skills 1 st Grade. Content Standard 9: Comprehension. Content Standard 8: Foundations of Reading Reading Goals by Skills 1 st Grade Content Standard 8: Foundations of Reading General Goal Name: Utilizing Concepts about Print SLE# Required Expectations R.8.1.1 Distinguish between letters, words and

More information

ArcHC_3D research case studies (FCT:PTDC/AUR/66476/2006) Casos de estudo do projecto ArcHC_3D (FCT:PTDC/AUR/66476/2006)

ArcHC_3D research case studies (FCT:PTDC/AUR/66476/2006) Casos de estudo do projecto ArcHC_3D (FCT:PTDC/AUR/66476/2006) ArcHC_3D research case studies (FCT:PTDC/AUR/66476/2006) Casos de estudo do projecto ArcHC_3D (FCT:PTDC/AUR/66476/2006) 1 Casa de Valflores - Loures 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Capela de S. Frutuoso

More information

DRA2 Word Analysis. correlated to. Virginia Learning Standards Grade 1

DRA2 Word Analysis. correlated to. Virginia Learning Standards Grade 1 DRA2 Word Analysis correlated to Virginia Learning Standards Grade 1 Quickly identify and generate words that rhyme with given words. Quickly identify and generate words that begin with the same sound.

More information

Text-To-Speech Technologies for Mobile Telephony Services

Text-To-Speech Technologies for Mobile Telephony Services Text-To-Speech Technologies for Mobile Telephony Services Paulseph-John Farrugia Department of Computer Science and AI, University of Malta Abstract. Text-To-Speech (TTS) systems aim to transform arbitrary

More information

An Arabic Text-To-Speech System Based on Artificial Neural Networks

An Arabic Text-To-Speech System Based on Artificial Neural Networks Journal of Computer Science 5 (3): 207-213, 2009 ISSN 1549-3636 2009 Science Publications An Arabic Text-To-Speech System Based on Artificial Neural Networks Ghadeer Al-Said and Moussa Abdallah Department

More information

Prelinguistic vocal behaviors. Stage 1 (birth-1 month) Stage 2 (2-3 months) Stage 4 (7-9 months) Stage 3 (4-6 months)

Prelinguistic vocal behaviors. Stage 1 (birth-1 month) Stage 2 (2-3 months) Stage 4 (7-9 months) Stage 3 (4-6 months) 3 stages of phonological development 1. Prelinguistic vocal behaviors 2. Phonology of the first 50 words 3. Emergence of rules Prelinguistic vocal behaviors Reflexive/vegetative sounds (birth-1 month)

More information

Prosody and Intonation / April 14, 2005 Ted Gibson

Prosody and Intonation / April 14, 2005 Ted Gibson Prosody and Intonation 9.59 / 24.905 April 14, 2005 Ted Gibson Prosody and Intonation Definition of prosody Intonation: pitch and boundaries Timing within intonation phrases Stress Intonational phrasing

More information

READING TEST RESULTS, STRENGTHS, NEEDS, MEASURABLE GOALS: EXAMPLES

READING TEST RESULTS, STRENGTHS, NEEDS, MEASURABLE GOALS: EXAMPLES READING TEST RESULTS, STRENGTHS, NEEDS, MEASURABLE GOALS: EXAMPLES NOTE SEVERAL DIFFERENT EXAMPLES OF STRENGTHS AND WEAKNESSES IN EACH AREA ARE PROVIDED AS EXAMPLES ONLY. THE IEP TEAM DECIDES HOW MANY

More information

Fountas and Pinnell Benchmark Assessment System (1 and 2): The Research Base

Fountas and Pinnell Benchmark Assessment System (1 and 2): The Research Base Fountas and Pinnell Benchmark Assessment System (1 and 2): The Research Base The Fountas and Pinnell Benchmark Assessment System consists of a series of carefully designed benchmark books that measure

More information

Portions have been extracted from this report to protect the identity of the student. RIT/NTID AURAL REHABILITATION REPORT Academic Year 2003 2004

Portions have been extracted from this report to protect the identity of the student. RIT/NTID AURAL REHABILITATION REPORT Academic Year 2003 2004 Portions have been extracted from this report to protect the identity of the student. Sessions: 9/03 5/04 Device: N24 cochlear implant Speech processors: 3G & Sprint RIT/NTID AURAL REHABILITATION REPORT

More information

Natural Language Processing using Machine Learning

Natural Language Processing using Machine Learning Natural Language Processing using Machine Learning Miguel Almeida, André Martins, Afonso Mendes Priberam Labs http://labs.priberam.com mba@priberam.com December 18, 2012 One of the easiest NLP problems

More information

The effect of mismatched recording conditions on human and automatic speaker recognition in forensic applications

The effect of mismatched recording conditions on human and automatic speaker recognition in forensic applications Forensic Science International 146S (2004) S95 S99 www.elsevier.com/locate/forsciint The effect of mismatched recording conditions on human and automatic speaker recognition in forensic applications A.

More information

Workshop Perceptual Effects of Filtering and Masking Introduction to Filtering and Masking

Workshop Perceptual Effects of Filtering and Masking Introduction to Filtering and Masking Workshop Perceptual Effects of Filtering and Masking Introduction to Filtering and Masking The perception and correct identification of speech sounds as phonemes depends on the listener extracting various

More information

Elementary English Pacing Guides for Henrico County Public Schools

Elementary English Pacing Guides for Henrico County Public Schools The revised Pacing Guide is the collaborative work of the 2013 Curriculum Committee, formed to critically consider the importance of the Curriculum as the foundation for all learning. With this in mind,

More information

Automatic Text Analysis Using Drupal

Automatic Text Analysis Using Drupal Automatic Text Analysis Using Drupal By Herman Chai Computer Engineering California Polytechnic State University, San Luis Obispo Advised by Dr. Foaad Khosmood June 14, 2013 Abstract Natural language processing

More information

The syllable as emerging unit of information, processing, production

The syllable as emerging unit of information, processing, production The syllable as emerging unit of information, processing, production September 27-29, 2012 Dartmouth College, Hanover NH Neukom Institute for Computational Science; Linguistics and Cognitive Science Program

More information

Email to Voice. Tips for Email to Broadcast

Email to Voice. Tips for Email to Broadcast Contents Email to Broadcast Services addresses... 2 Job Name... 2 Email to Text To Speech... 2 Voice Software... 3 Write out the words... 4 Names... 4 Punctuation... 4 Pauses... 4 Vowels... 4 Telephone

More information

SYNTHESISED SPEECH WITH UNIT SELECTION

SYNTHESISED SPEECH WITH UNIT SELECTION Institute of Phonetic Sciences, University of Amsterdam, Proceedings 24 (2001), 57-63. SYNTHESISED SPEECH WITH UNIT SELECTION Creating a restricted domain speech corpus for Dutch Betina Simonsen, Esther

More information

Grade 1 LA. 1. 1. 1. 1. Subject Grade Strand Standard Benchmark. Florida K-12 Reading and Language Arts Standards 27

Grade 1 LA. 1. 1. 1. 1. Subject Grade Strand Standard Benchmark. Florida K-12 Reading and Language Arts Standards 27 Grade 1 LA. 1. 1. 1. 1 Subject Grade Strand Standard Benchmark Florida K-12 Reading and Language Arts Standards 27 Grade 1: Reading Process Concepts of Print Standard: The student demonstrates knowledge

More information

Carla Simões, t-carlas@microsoft.com. Speech Analysis and Transcription Software

Carla Simões, t-carlas@microsoft.com. Speech Analysis and Transcription Software Carla Simões, t-carlas@microsoft.com Speech Analysis and Transcription Software 1 Overview Methods for Speech Acoustic Analysis Why Speech Acoustic Analysis? Annotation Segmentation Alignment Speech Analysis

More information

Applications of Portuguese Speech and Language Technologies - Propor 2008 Special Session. Promoted by: Microsoft Language Development Center

Applications of Portuguese Speech and Language Technologies - Propor 2008 Special Session. Promoted by: Microsoft Language Development Center 1 Applications of Portuguese Speech and Language Technologies - Propor 2008 Special Session Hosted by: Universidade de Aveiro Promoted by: Microsoft Language Development Center 2 Propor 2008 Special Session

More information

The Effect of Long-Term Use of Drugs on Speaker s Fundamental Frequency

The Effect of Long-Term Use of Drugs on Speaker s Fundamental Frequency The Effect of Long-Term Use of Drugs on Speaker s Fundamental Frequency Andrey Raev 1, Yuri Matveev 1, Tatiana Goloshchapova 2 1 Speech Technology Center, St. Petersburg, RUSSIA {raev, matveev}@speechpro.com

More information

HCAHPS Quality Assurance Guidelines V9.0 Technical Corrections and Clarifications Revised August 2014

HCAHPS Quality Assurance Guidelines V9.0 Technical Corrections and Clarifications Revised August 2014 Subsequent to the release of the HCAHPS Quality Assurance Guidelines V9.0 (QAG V9.0), it has been determined that there are specific content items that require correction, addition and/or further clarification.

More information

FUNCTIONAL SKILLS ENGLISH - WRITING LEVEL 2

FUNCTIONAL SKILLS ENGLISH - WRITING LEVEL 2 FUNCTIONAL SKILLS ENGLISH - WRITING LEVEL 2 MARK SCHEME Instructions to marker There are 30 marks available for each of the three tasks, which should be marked separately, resulting in a total of 90 marks.

More information

Customer Relationship Management Systems why many large companies do not have them?

Customer Relationship Management Systems why many large companies do not have them? Customer Relationship Management Systems why many large companies do not have them? Manuela Cunha 1 4, João Varajão 2,3, Daniela Santana 2, Isabel Bentes 2 1 Instituto Politécnico do Cávado e do Ave, Portugal

More information

Learning Today Smart Tutor Supports English Language Learners

Learning Today Smart Tutor Supports English Language Learners Learning Today Smart Tutor Supports English Language Learners By Paolo Martin M.A. Ed Literacy Specialist UC Berkley 1 Introduction Across the nation, the numbers of students with limited English proficiency

More information

Things to remember when transcribing speech

Things to remember when transcribing speech Notes and discussion Things to remember when transcribing speech David Crystal University of Reading Until the day comes when this journal is available in an audio or video format, we shall have to rely

More information

TExES English Language Arts and Reading 4 8 (117) Test at a Glance

TExES English Language Arts and Reading 4 8 (117) Test at a Glance TExES English Language Arts and Reading 4 8 (117) Test at a Glance See the test preparation manual for complete information about the test along with sample questions, study tips and preparation resources.

More information

Myanmar Continuous Speech Recognition System Based on DTW and HMM

Myanmar Continuous Speech Recognition System Based on DTW and HMM Myanmar Continuous Speech Recognition System Based on DTW and HMM Ingyin Khaing Department of Information and Technology University of Technology (Yatanarpon Cyber City),near Pyin Oo Lwin, Myanmar Abstract-

More information

MODELING OF USER STATE ESPECIALLY OF EMOTIONS. Elmar Nöth. University of Erlangen Nuremberg, Chair for Pattern Recognition, Erlangen, F.R.G.

MODELING OF USER STATE ESPECIALLY OF EMOTIONS. Elmar Nöth. University of Erlangen Nuremberg, Chair for Pattern Recognition, Erlangen, F.R.G. MODELING OF USER STATE ESPECIALLY OF EMOTIONS Elmar Nöth University of Erlangen Nuremberg, Chair for Pattern Recognition, Erlangen, F.R.G. email: noeth@informatik.uni-erlangen.de Dagstuhl, October 2001

More information

Pronunciation in English - High Beginning+ Pronunciation in English - Intermediate+

Pronunciation in English - High Beginning+ Pronunciation in English - Intermediate+ Teacher's Guide to Pronunciation in English - High Beginning+ Pronunciation in English - Intermediate+ User Management System Included for all schools at no additional cost Feedback from students After

More information

FSD Kindergarten READING

FSD Kindergarten READING College and Career Readiness Anchor Standards for Reading Read closely to determine what the text says explicitly and to make logical inferences from it; cite specific textual evidence when writing or

More information

Aspects of North Swedish intonational phonology. Bruce, Gösta

Aspects of North Swedish intonational phonology. Bruce, Gösta Aspects of North Swedish intonational phonology. Bruce, Gösta Published in: Proceedings from Fonetik 3 ; Phonum 9 Published: 3-01-01 Link to publication Citation for published version (APA): Bruce, G.

More information

The effects of non-native English speaking EFL teachers accents on their willingness to teach pronunciation

The effects of non-native English speaking EFL teachers accents on their willingness to teach pronunciation The effects of non-native English speaking EFL teachers accents on their willingness to teach pronunciation Margaret Hogan Facultad de Idiomas, UABC, Mexico ACTA, July 2012 Outline 1. Introduction 2. Research

More information

WHICH TYPE OF GRAPH SHOULD YOU CHOOSE?

WHICH TYPE OF GRAPH SHOULD YOU CHOOSE? PRESENTING GRAPHS WHICH TYPE OF GRAPH SHOULD YOU CHOOSE? CHOOSING THE RIGHT TYPE OF GRAPH You will usually choose one of four very common graph types: Line graph Bar graph Pie chart Histograms LINE GRAPHS

More information

Scope and Sequence - Synthetic Phonics Schedule

Scope and Sequence - Synthetic Phonics Schedule Correspondences () Kindy/Prep/Pre-Primary Kindy/Prep/Pre-Primary Term 1 Basic Code Power 1 Getting to Grips with Handwriting s m c t g p a o I, the, was, to, are, she Reading and beginning to spell Vocabulary

More information

In: Proceedings of RECPAD 2002-12th Portuguese Conference on Pattern Recognition June 27th- 28th, 2002 Aveiro, Portugal

In: Proceedings of RECPAD 2002-12th Portuguese Conference on Pattern Recognition June 27th- 28th, 2002 Aveiro, Portugal Paper Title: Generic Framework for Video Analysis Authors: Luís Filipe Tavares INESC Porto lft@inescporto.pt Luís Teixeira INESC Porto, Universidade Católica Portuguesa lmt@inescporto.pt Luís Corte-Real

More information

20 by Renaissance Learning, Inc. All rights reserved. Printed in the United States of America.

20 by Renaissance Learning, Inc. All rights reserved. Printed in the United States of America. R4 Advanced Technology for, Renaissance, Renaissance Learning, Renaissance Place, STAR Early Literacy, STAR Math, and STAR Reading, are trademarks of Renaissance Learning, Inc., and its subsidiaries, registered,

More information

Corpus Driven Malayalam Text-to-Speech Synthesis for Interactive Voice Response System

Corpus Driven Malayalam Text-to-Speech Synthesis for Interactive Voice Response System Corpus Driven Malayalam Text-to-Speech Synthesis for Interactive Voice Response System Arun Soman, Sachin Kumar S., Hemanth V. K., M. Sabarimalai Manikandan, K. P. Soman Centre for Excellence in Computational

More information

SEDAT ERDOĞAN. Ses, Dil, Edebiyat, Öğrenim... TEMEL İNGİLİZCE. Ses dilin temelidir, özüdür... Türkiye de ses öğrenimi

SEDAT ERDOĞAN. Ses, Dil, Edebiyat, Öğrenim... TEMEL İNGİLİZCE. Ses dilin temelidir, özüdür... Türkiye de ses öğrenimi SEDAT ERDOĞAN Ses, Dil, Edebiyat, Öğrenim... TEMEL İNGİLİZCE Ses dilin temelidir, özüdür... Türkiye de ses öğrenimi olmadığından dil öğrenimi zayıftır, kötüdür... PRONUNCIATION HINTS */a/ vowel sound is

More information

Colaboradores: Contreras Terreros Diana Ivette Alumna LELI N de cuenta: 191351. Ramírez Gómez Roberto Egresado Programa Recuperación de pasantía.

Colaboradores: Contreras Terreros Diana Ivette Alumna LELI N de cuenta: 191351. Ramírez Gómez Roberto Egresado Programa Recuperación de pasantía. Nombre del autor: Maestra Bertha Guadalupe Paredes Zepeda. bparedesz2000@hotmail.com Colaboradores: Contreras Terreros Diana Ivette Alumna LELI N de cuenta: 191351. Ramírez Gómez Roberto Egresado Programa

More information

Curriculum Vitae. January, 2005

Curriculum Vitae. January, 2005 Curriculum Vitae January, 2005 Paulo Jorge Marques de Oliveira Ribeiro Pereira Invited Assistant Lecturer Management Department School of Economics and Management University of Minho Office: University

More information

Chapter 5. English Words and Sentences. Ching Kang Liu Language Center National Taipei University

Chapter 5. English Words and Sentences. Ching Kang Liu Language Center National Taipei University Chapter 5 English Words and Sentences Ching Kang Liu Language Center National Taipei University 1 Citation form The strong form and the weak form 1. The form in which a word is pronounced when it is considered

More information

Standards and progression point examples

Standards and progression point examples English Progressing towards Foundation Progression Point 0.5 At 0.5, a student progressing towards the standard at Foundation may, for example: explain the directionality of printed texts (ACELA1433 Concepts

More information

Priberam s question answering system for Portuguese

Priberam s question answering system for Portuguese Priberam Informática Av. Defensores de Chaves, 32 3º Esq. 1000-119 Lisboa, Portugal Tel.: +351 21 781 72 60 / Fax: +351 21 781 72 79 Summary Priberam s question answering system for Portuguese Carlos Amaral,

More information

Crystal Tower 1-2-27 Shiromi, Chuo-ku, Osaka 540-6025 JAPAN. ffukumoto,simohata,masui,sasakig@kansai.oki.co.jp

Crystal Tower 1-2-27 Shiromi, Chuo-ku, Osaka 540-6025 JAPAN. ffukumoto,simohata,masui,sasakig@kansai.oki.co.jp Oki Electric Industry : Description of the Oki System as Used for MET-2 J. Fukumoto, M. Shimohata, F. Masui, M. Sasaki Kansai Lab., R&D group Oki Electric Industry Co., Ltd. Crystal Tower 1-2-27 Shiromi,

More information

Micro blogs Oriented Word Segmentation System

Micro blogs Oriented Word Segmentation System Micro blogs Oriented Word Segmentation System Yijia Liu, Meishan Zhang, Wanxiang Che, Ting Liu, Yihe Deng Research Center for Social Computing and Information Retrieval Harbin Institute of Technology,

More information

Analysis and Synthesis of Hypo and Hyperarticulated Speech

Analysis and Synthesis of Hypo and Hyperarticulated Speech Analysis and Synthesis of and articulated Speech Benjamin Picart, Thomas Drugman, Thierry Dutoit TCTS Lab, Faculté Polytechnique (FPMs), University of Mons (UMons), Belgium {benjamin.picart,thomas.drugman,thierry.dutoit}@umons.ac.be

More information

Experiments with Signal-Driven Symbolic Prosody for Statistical Parametric Speech Synthesis

Experiments with Signal-Driven Symbolic Prosody for Statistical Parametric Speech Synthesis Experiments with Signal-Driven Symbolic Prosody for Statistical Parametric Speech Synthesis Fabio Tesser, Giacomo Sommavilla, Giulio Paci, Piero Cosi Institute of Cognitive Sciences and Technologies, National

More information

PROGRESS MONITORING CHECKLIST FOR ENGLISH LANGUAGE LEARNERS (ELL)

PROGRESS MONITORING CHECKLIST FOR ENGLISH LANGUAGE LEARNERS (ELL) LISTENING Standard : Students demonstrate competence in listening as a tool for learning and comprehension. Proficiency Level I: Students at this level are beginning to understand short utterances. They

More information

Bachelors of Science Program in Communication Disorders and Sciences:

Bachelors of Science Program in Communication Disorders and Sciences: Bachelors of Science Program in Communication Disorders and Sciences: Mission: The SIUC CDS program is committed to multiple complimentary missions. We provide support for, and align with, the university,

More information

Interface Design for Mobile Devices Workshop [IDMD]

Interface Design for Mobile Devices Workshop [IDMD] Interface Design for Mobile Devices Workshop [IDMD] Future Places Porto Mónica Mendes & Nuno Correia Porto October 2009 Interface Design for Mobile Devices Workshop Mónica Mendes & Nuno Correia Future

More information

Module Catalogue for the Bachelor Program in Computational Linguistics at the University of Heidelberg

Module Catalogue for the Bachelor Program in Computational Linguistics at the University of Heidelberg Module Catalogue for the Bachelor Program in Computational Linguistics at the University of Heidelberg March 1, 2007 The catalogue is organized into sections of (1) obligatory modules ( Basismodule ) that

More information

62 Hearing Impaired MI-SG-FLD062-02

62 Hearing Impaired MI-SG-FLD062-02 62 Hearing Impaired MI-SG-FLD062-02 TABLE OF CONTENTS PART 1: General Information About the MTTC Program and Test Preparation OVERVIEW OF THE TESTING PROGRAM... 1-1 Contact Information Test Development

More information

Efficient Techniques for Improved Data Classification and POS Tagging by Monitoring Extraction, Pruning and Updating of Unknown Foreign Words

Efficient Techniques for Improved Data Classification and POS Tagging by Monitoring Extraction, Pruning and Updating of Unknown Foreign Words , pp.290-295 http://dx.doi.org/10.14257/astl.2015.111.55 Efficient Techniques for Improved Data Classification and POS Tagging by Monitoring Extraction, Pruning and Updating of Unknown Foreign Words Irfan

More information

Elementary Statistics. Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination

Elementary Statistics. Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination What is a Scatter Plot? A Scatter Plot is a plot of ordered pairs (x, y) where the horizontal axis is used

More information

The Production of English Noun-verb Stress Contrast in Rising Intonation by Taiwanese EFL Learners 國立中山大學外文所程筱雯 ABSTRACT

The Production of English Noun-verb Stress Contrast in Rising Intonation by Taiwanese EFL Learners 國立中山大學外文所程筱雯 ABSTRACT The Production of English Noun-verb Stress Contrast in Rising Intonation by Taiwanese EFL Learners 國立中山大學外文所程筱雯 ABSTRACT The present study aims to investigate how the acoustic cues (i.e., mean pitch, duration,

More information

Modern foreign languages

Modern foreign languages Modern foreign languages Programme of study for key stage 3 and attainment targets (This is an extract from The National Curriculum 2007) Crown copyright 2007 Qualifications and Curriculum Authority 2007

More information

Towards automatic speech summarization without transcription

Towards automatic speech summarization without transcription Towards automatic speech summarization without transcription G. Gravier, A. Muscariello, C. Guinaudeau, F. Bimbot nom.prenom@irisa.fr IRISA & INRIA Rennes The classical approach Use ASR as a transducer

More information

How to work with a video clip in EJA English classes?

How to work with a video clip in EJA English classes? How to work with a video clip in EJA English classes? Introduction Working with projects implies to take into account the students interests and needs, to build knowledge collectively, to focus on the

More information

Stricture and Nasal Place Assimilation. Jaye Padgett

Stricture and Nasal Place Assimilation. Jaye Padgett Stricture and Nasal Place Assimilation Jaye Padgett Stricture Stricture features determine the degree of constriction in the vocal tract; [son], [ cons], [cont] [-cont]: Verschluss im mediosagittalen Bereich

More information

Grid e-services for Multi-Layer SOM Neural Network Simulation

Grid e-services for Multi-Layer SOM Neural Network Simulation Grid e-services for Multi-Layer SOM Neural Network Simulation,, Rui Silva Faculdade de Engenharia 4760-108 V. N. Famalicão, Portugal {rml,rsilva}@fam.ulusiada.pt 2007 Outline Overview Multi-Layer SOM Background

More information

. Niparko, J. K. (2006). Speech Recognition at 1-Year Follow-Up in the Childhood

. Niparko, J. K. (2006). Speech Recognition at 1-Year Follow-Up in the Childhood Psychology 230: Research Methods Lab A Katie Berg, Brandon Geary, Gina Scharenbroch, Haley Schmidt, & Elizabeth Stevens Introduction: Overview: A training program, under the lead of Professor Jeremy Loebach,

More information

LANGUAGE LEARNING IN A SPECIAL EDUCATION ENVIRONMENT. Oscar Saz (CMU Post-Doc) PSLC-CF

LANGUAGE LEARNING IN A SPECIAL EDUCATION ENVIRONMENT. Oscar Saz (CMU Post-Doc) PSLC-CF LANGUAGE LEARNING IN A SPECIAL EDUCATION ENVIRONMENT Oscar Saz (CMU Post-Doc) PSLC-CF Overview 2 Brief introduction: Language learning in special education Development of computer tutors for speech therapy

More information

On the production of contrastive accents in German

On the production of contrastive accents in German On the production of contrastive accents in German Frank Kügler & Anja Gollrad Potsdam University Contrastiveness Concept of contrastiveness has received much attention in the pycholinguistic research

More information

NATURAL SOUNDING TEXT-TO-SPEECH SYNTHESIS BASED ON SYLLABLE-LIKE UNITS SAMUEL THOMAS MASTER OF SCIENCE

NATURAL SOUNDING TEXT-TO-SPEECH SYNTHESIS BASED ON SYLLABLE-LIKE UNITS SAMUEL THOMAS MASTER OF SCIENCE NATURAL SOUNDING TEXT-TO-SPEECH SYNTHESIS BASED ON SYLLABLE-LIKE UNITS A THESIS submitted by SAMUEL THOMAS for the award of the degree of MASTER OF SCIENCE (by Research) DEPARTMENT OF COMPUTER SCIENCE

More information

Houghton Mifflin Harcourt StoryTown Grade 1. correlated to the. Common Core State Standards Initiative English Language Arts (2010) Grade 1

Houghton Mifflin Harcourt StoryTown Grade 1. correlated to the. Common Core State Standards Initiative English Language Arts (2010) Grade 1 Houghton Mifflin Harcourt StoryTown Grade 1 correlated to the Common Core State Standards Initiative English Language Arts (2010) Grade 1 Reading: Literature Key Ideas and details RL.1.1 Ask and answer

More information

SOME ASPECTS OF ASR TRANSCRIPTION BASED UNSUPERVISED SPEAKER ADAPTATION FOR HMM SPEECH SYNTHESIS

SOME ASPECTS OF ASR TRANSCRIPTION BASED UNSUPERVISED SPEAKER ADAPTATION FOR HMM SPEECH SYNTHESIS SOME ASPECTS OF ASR TRANSCRIPTION BASED UNSUPERVISED SPEAKER ADAPTATION FOR HMM SPEECH SYNTHESIS Bálint Tóth, Tibor Fegyó, Géza Németh Department of Telecommunications and Media Informatics Budapest University

More information

of knowledge that is characteristic of the profession and is taught at professional schools. An important author in establishing this notion was

of knowledge that is characteristic of the profession and is taught at professional schools. An important author in establishing this notion was Mathematics teacher education and professional development João Pedro da Ponte jponte@fc.ul.pt Grupo de Investigação DIFMAT Centro de Investigação em Educação e Departamento de Educação Faculdade de Ciências

More information

dm106 TEXT MINING FOR CUSTOMER RELATIONSHIP MANAGEMENT: AN APPROACH BASED ON LATENT SEMANTIC ANALYSIS AND FUZZY CLUSTERING

dm106 TEXT MINING FOR CUSTOMER RELATIONSHIP MANAGEMENT: AN APPROACH BASED ON LATENT SEMANTIC ANALYSIS AND FUZZY CLUSTERING dm106 TEXT MINING FOR CUSTOMER RELATIONSHIP MANAGEMENT: AN APPROACH BASED ON LATENT SEMANTIC ANALYSIS AND FUZZY CLUSTERING ABSTRACT In most CRM (Customer Relationship Management) systems, information on

More information

Technologies for Voice Portal Platform

Technologies for Voice Portal Platform Technologies for Voice Portal Platform V Yasushi Yamazaki V Hitoshi Iwamida V Kazuhiro Watanabe (Manuscript received November 28, 2003) The voice user interface is an important tool for realizing natural,

More information

Automatic Transcription of Continuous Speech using Unsupervised and Incremental Training

Automatic Transcription of Continuous Speech using Unsupervised and Incremental Training INTERSPEECH-2004 1 Automatic Transcription of Continuous Speech using Unsupervised and Incremental Training G.L. Sarada, N. Hemalatha, T. Nagarajan, Hema A. Murthy Department of Computer Science and Engg.,

More information

Pronunciation in English

Pronunciation in English The Electronic Journal for English as a Second Language Pronunciation in English March 2013 Volume 16, Number 4 Title Level Publisher Type of product Minimum Hardware Requirements Software Requirements

More information

Technology for English Language Learners

Technology for English Language Learners Technology for English Language Learners PreK Adult A Multisensory Approach to Learning early literacy and mathematics reading to learn becoming Lifelong learners Grades PreK 5 Support for beginning readers

More information

COURSE SYLLABUS ESU 561 ASPECTS OF THE ENGLISH LANGUAGE. Fall 2014

COURSE SYLLABUS ESU 561 ASPECTS OF THE ENGLISH LANGUAGE. Fall 2014 COURSE SYLLABUS ESU 561 ASPECTS OF THE ENGLISH LANGUAGE Fall 2014 EDU 561 (85515) Instructor: Bart Weyand Classroom: Online TEL: (207) 985-7140 E-Mail: weyand@maine.edu COURSE DESCRIPTION: This is a practical

More information

AUDIMUS.media: A Broadcast News Speech Recognition System for the European Portuguese Language

AUDIMUS.media: A Broadcast News Speech Recognition System for the European Portuguese Language AUDIMUS.media: A Broadcast News Speech Recognition System for the European Portuguese Language Hugo Meinedo, Diamantino Caseiro, João Neto, and Isabel Trancoso L 2 F Spoken Language Systems Lab INESC-ID

More information

Using telehealth to deliver speech treatment for Parkinson s into the home: Outcomes & satisfaction

Using telehealth to deliver speech treatment for Parkinson s into the home: Outcomes & satisfaction Using telehealth to deliver speech treatment for Parkinson s into the home: Outcomes & satisfaction Deborah Theodoros PhD Anne Hill PhD Trevor Russell PhD Telerehabilitation Research Unit Parkinson s Australia

More information

COMPUTATIONAL DATA ANALYSIS FOR SYNTAX

COMPUTATIONAL DATA ANALYSIS FOR SYNTAX COLING 82, J. Horeck~ (ed.j North-Holland Publishing Compa~y Academia, 1982 COMPUTATIONAL DATA ANALYSIS FOR SYNTAX Ludmila UhliFova - Zva Nebeska - Jan Kralik Czech Language Institute Czechoslovak Academy

More information