An Analysis of Speech Disfluency on the Ellen Degeneres Show
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The Humour of Greyson Chance (To Mark the Third Anniversary of the Beginning of His Career)
1 The Humour Of Greyson Chance (to mark the third anniversary of the beginning of his career) 28 April 2010, when he posted his cover of Paparazzi and his own song Broken Hearts to YouTube, is usually regarded as the beginning of his career. A year ago (on 30 April 2012), during a private function in Hongkong, he recounted that his fans had tweeted to him two days previously ’Two years, two years, two years’ and that he had wondered ‘What’s two years?’ which provoked merriment among the audience. Upon this, he performed a liberally modified version of his cover of Lady Gaga’s Paparazzi, originally the commencement of his career: http://www.youtube.com/watch?v=WNZFilwkfvU It is reassuring that his fans remind him of this anniversary when he himself fails to remember it! This was the time that followed his (band-accompanied) first concert tour in South-East Asia, when he stayed on for a few weeks to perform solo and give interviews. His most frequently varied song, Waiting Outside The Lines, he often interpreted in an exuberant manner, winding up by repeating the ‘wo-o’ for up to forty seconds. Unfortunately, the videos are often of a bad quality: 24 April in Taiwan: http://www.youtube.com/watch?v=iL2Qa_6XGZg 20 April in Hongkong: http://www.youtube.com/watch?v=fnsZkuCKwUs 4 May in Bangkok: http://www.youtube.com/watch?v=LHI65bMUj9o These videos show clearly that he entertains not only his fans, but also himself, and that it is one of his basic characteristics to vary the songs from each perfomance to the next. -
Issue How Detroit Let Siena Liggins Unleash Her Queer Superpowers on Her Debut Album
as a MICHIGAN'S LGBTQ+ NEWS SOURCE SINCE 1993 SUMMER OF PRIDE BOY FROM MICHIGAN John Grant on His Most Personal Album Yet PLUS LIVE SHOWS RETURN A Local Assault on 11 Must-See Artists Two Gay Men. Now, Coming To Town How to Heal The Queer Music Issue How Detroit Let Siena Liggins Unleash Her Queer Superpowers on Her Debut Album PRIDESOURCE.COM JULY 8, 2021 | VOL. 2928 | FREE 18 24 28 2 BTL | July 8, 2021 www.PrideSource.com 4 5 Queer Things You Can Do Right Now 6 Spotify Commissions Ruth Ellis Center Mural to Celebrate Queer Community VOL. 2928 • JULY 8, 2021 ISSUE 1178 10 Affirmations Telethon and Funding Campaign Raises $125,775, Jay Kaplan PRIDE SOURCE MEDIA GROUP Wins Jan Stevenson Award www.pridesource.com 10 How Do We Heal After an Anti-LGBTQ+ Hate Crime? Phone 734-263-1476 PUBLISHERS 12 Outed on the Job: Lesbian Prison Officer Sues Michigan Prison System Benjamin Jenkins Following ‘Horrible’ Harassment [email protected] 18 Publishers Emeritus: Jan Stevenson & Susan Horowitz 12 Transmissions: Musing on Loss DIRECTOR OF OPERATIONS 13 Parting Glances: OZ Updated Tom Wesley [email protected] 14 Michigan Supreme Court to Decide on Elliott-Larsen Civil Rights Case EDITORIAL Editorial Director 16 As Masc Lesbian As She Wants to Be Chris Azzopardi [email protected] 18 At Long Last, Live Shows Return to Michigan News & Feature Editor Eve Kucharski 20 John Grant on His Most Personal Album Yet [email protected] 22 Keep Your Pride Season Going News & Feature Writers With These 8 Queer Artists (and Allies Lawrence Ferber, Ellen Knoppow, Jason A. -
Recurrent Neural Networks in Speech Disfluency Detection And
Recurrent Neural Networks in Speech Disfluency Detection and Punctuation Prediction Master’s Thesis Matthias Reisser 1538923 At the Department of Informatics Interactive Systems Lab (ISL) Institute of Anthropomatics and Robotics Reviewer: Prof. Dr. Alexander Waibel Second reviewer: Prof. Dr. J. Marius Zöllner Advisor: Kevin Kilgour, Ph.D Second advisor: Eunah Cho 15th of November 2015 KIT – University of the State of Baden-Wuerttemberg and National Laboratory of the Helmholtz Association www.kit.edu Abstract With the increased performance of automatic speech recognition systems in recent years, applications that process spoken speech transcripts become in- creasingly relevant. These applications, such as automated machine transla- tion systems, dialogue systems or information extraction systems, usually are trained on large amount of text corpora. Since acquiring, manually transcribing and annotating spoken language transcripts is prohibitively expensive, natural language processing systems are trained on existing text corpora of well-written texts. However, since spoken language transcripts, as they are generated by automatic speech recognition systems, are full of speech disfluencies and lack punctuation marks as well as sentence boundaries, there is a mismatch be- tween the training corpora and the actual use case. In order to achieve high performance on spoken language transcripts, it is necessary to detect and re- move these disfluencies, as well as insert punctuation marks prior to processing them. The focus of this thesis therefore lies in addressing the tasks of disfluency de- tection and punctuation prediction on two data sets of spontaneous speech: The multi-party meeting data set (Cho, Niehues, & Waibel, 2014) and the switchboard data set of telephone conversations (Godfrey et al., 1992). -
A Corpus-Based Study of Speech Fluency Across English Dialects
1 A CORPUS-BASED STUDY OF SPEECH FLUENCY ACROSS ENGLISH DIALECTS A thesis submitted in partial fulfillment of the Requirements for the degree of Master of Science in Speech and Language Sciences In the University of Canterbury By Nandini Shanmukha University of Canterbury 2017 2 Table of Contents List of Figures .................................................................................................................... 5 List of Tables ...................................................................................................................... 6 Acknowledgements ............................................................................................................ 7 Abstract: ............................................................................................................................. 8 1. BACKGROUND ........................................................................................................... 9 1.1. Speech Fluency vs Disfluency ........................................................................... 10 1.2. Normal disfluencies Vs Stuttering-like disfluencies: ...................................... 11 1.2.1. Normative fluency data ................................................................................. 11 1.3. Contributing factors to speech disfluency: ...................................................... 13 1.3.1. Situational factors: ........................................................................................ 14 1.3.2. Topic familiarity:.......................................................................................... -
NWAV 46 Booklet-Oct29
1 PROGRAM BOOKLET October 29, 2017 CONTENTS • The venue and the town • The program • Welcome to NWAV 46 • The team and the reviewers • Sponsors and Book Exhibitors • Student Travel Awards https://english.wisc.edu/nwav46/ • Abstracts o Plenaries Workshops o nwav46 o Panels o Posters and oral presentations • Best student paper and poster @nwav46 • NWAV sexual harassment policy • Participant email addresses Look, folks, this is an electronic booklet. This Table of Contents gives you clues for what to search for and we trust that’s all you need. 2 We’ll have buttons with sets of pronouns … and some with a blank space to write in your own set. 3 The venue and the town We’re assuming you’ll navigate using electronic devices, but here’s some basic info. Here’s a good campus map: http://map.wisc.edu/. The conference will be in Union South, in red below, except for Saturday talks, which will be in the Brogden Psychology Building, just across Johnson Street to the northeast on the map. There are a few places to grab a bite or a drink near Union South and the big concentration of places is on and near State Street, a pedestrian zone that runs east from Memorial Library (top right). 4 The program 5 NWAV 46 2017 Madison, WI Thursday, November 2nd, 2017 12:00 Registration – 5th Quarter Room, Union South pm-6:00 pm Industry Landmark Northwoods Agriculture 1:00- Progress in regression: Discourse analysis for Sociolinguistics and Texts as data 3:00 Statistical and practical variationists forensic speech sources for improvements to Rbrul science: Knowledge- -
Exploring the Role of Fillers in the Automatic Prediction of a Speaker's
How Confident are You? Exploring the Role of Fillers in the Automatic Prediction of a Speaker’s Confidence Tanvi Dinkar, Ioana Vasilescu, Catherine Pelachaud, Chloé Clavel To cite this version: Tanvi Dinkar, Ioana Vasilescu, Catherine Pelachaud, Chloé Clavel. How Confident are You? Ex- ploring the Role of Fillers in the Automatic Prediction of a Speaker’s Confidence. Workshop sur les Affects, Compagnons artificiels et Interactions, CNRS, Université Toulouse Jean Jaurès, Université de Bordeaux, Jun 2020, Saint Pierre d’Oléron, France. hal-02933476 HAL Id: hal-02933476 https://hal.inria.fr/hal-02933476 Submitted on 8 Sep 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. How Confident are You? Exploring the Role of Fillers in the Automatic Prediction of a Speaker’s Confidence Tanvi Dinkar Ioana Vasilescu [email protected] [email protected] Institut Mines-Telecom, Telecom Paris, CNRS-LTCI, Paris, LIMSI, CNRS, Université Paris-Saclay, Orsay, France France Catherine Pelachaud Chloé Clavel [email protected] [email protected] CNRS-ISIR, UPMC, Paris, France Institut Mines-Telecom, Telecom Paris, CNRS-LTCI, Paris, France ABSTRACT structure of their utterance, such as in their (difficulties of) selec- “Fillers", example “um" in English, have been linked to the “Feel- tion of appropriate vocabulary while maintaining their turn (in ing of Another’s Knowing (FOAK)" or the listener’s perception of dialogue). -
Hit Makers Greyson Chance and Emblem3 Join All Star Line up at T.J
FOR IMMEDIATE RELEASE PRESS CONTACTS: Kristin Loretta Ketchum [email protected] Kate Fitzpatrick T.J. Martell Foundation, Communication Consultant [email protected] HIT MAKERS GREYSON CHANCE AND EMBLEM3 JOIN ALL STAR LINE UP AT T.J. MARTELL FOUNDATION’S 14TH ANNUAL FAMILY DAY HONORING PARADIGM’S MARTY DIAMOND AND FAMILY Greyson Chance and Emblem3 to perform along with Jason Mraz, Ed Sheeran and Austin Mahone at Family Day Event on September 15, 2013 in NYC New York, NY – (August 1, 2013) – The T.J. Martell Foundation is proud to announce the addition of Greyson Chance and Emblem3 to their impressive lineup of artists for its 14th Annual Family Day on Sunday, September 15th, 2013 at Roseland Ballroom in New York City. "I am honored and excited to be performing for an organization that truly helps our society," says Greyson Chance who, at fifteen years old, has already had a number one single, performed live on Ellen and Good Morning America and has shared stages with iCarly’s Miranda Cosgrove and Big Time Rush, previous Family Day honorees. As the breakout band on the hit show X Factor, amassing over 15 million YouTube views, Emblem3 is another amazing addition to this year’s event. According to the band members, "We are so excited to be performing at this year's Family Day with such an incredible lineup of artists supporting the T.J. Martell Foundation. We are stoked to be able to do our part to help in the fight against leukemia, cancer and AIDS." Joining Chance and Emblem3 at Family Day is multi Grammy-award winning singer Jason Mraz who will perform live along with Ed Sheeran and rising pop star Austin Mahone. -
Automatic Detection of Sentence Boundaries, Disfluencies, And
Automatic Detection of Sentence Boundaries, Disfluencies, and Conversational Fillers in Spontaneous Speech Joungbum Kim A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering University of Washington 2004 Program Authorized to Offer Degree: Electrical Engineering University of Washington Graduate School This is to certify that I have examined this copy of a master's thesis by Joungbum Kim and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Committee Members: Mari Ostendorf Katrin Kirchhoff Date: In presenting this thesis in partial fulfillment of the requirements for a Master's degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of this thesis is allowable only for scholarly purposes, consistent with \fair use" as prescribed in the U.S. Copyright Law. Any other reproduction for any purpose or by any means shall not be allowed without my written permission. Signature Date University of Washington Abstract Automatic Detection of Sentence Boundaries, Disfluencies, and Conversational Fillers in Spontaneous Speech Joungbum Kim Chair of Supervisory Committee: Professor Mari Ostendorf Electrical Engineering Ongoing research on improving the performance of speech-to-text (STT) systems has the potential to provide high quality machine transcription of human speech in the future. However, even if such a perfect STT system were available, readability of transcripts of spontaneous speech as well as their usability in natural language processing systems are likely to be low, since such transcripts lack segmentations and since spontaneous speech contains disfluencies and conversational fillers. -
Pronunciation and Disfluency Modeling for Expressive Speech Synthesis Raheel Qader
Pronunciation and disfluency modeling for expressive speech synthesis Raheel Qader To cite this version: Raheel Qader. Pronunciation and disfluency modeling for expressive speech synthesis. Artificial Intelligence [cs.AI]. Université Rennes 1, 2017. English. NNT : 2017REN1S076. tel-01668014v2 HAL Id: tel-01668014 https://hal.inria.fr/tel-01668014v2 Submitted on 15 Feb 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. N o d’ordre : 00000 ANNÉE 2017 THÈSE / UNIVERSITÉ DE RENNES 1 sous le sceau de l’Université Bretagne Loire pour le grade de DOCTEUR DE L’UNIVERSITÉ DE RENNES 1 Mention : Informatique École doctorale Matisse présentée par Raheel QADER préparée à l’unité de recherche IRISA – UMR6074 Institut de Recherche en Informatique et Système Aléatoires École Nationale Supérieure des Sciences Appliquées et de Technologie Soutenance de thèse envisagée à Lannion Pronunciation le 31 mars 2017 and disfluency devant le jury composé de : Simon KING modeling for ex- Full professor at the university of Edinburgh / Rapporteur Spyros RAPTIS Research director -
Worldcharts TOP 200 Vom 13.06.2016
CHARTSSERVICE – WORLDCHARTS – TOP 200 NO. 860 – 13.06.2016 PL VW WO PK ARTIST SONG 1 1 6 1 JUSTIN TIMBERLAKE can't stop the feeling! 2 2 7 1 CALVIN HARRIS ft. RIHANNA this is what you came for 3 3 10 1 DRAKE ft. WIZKID & KYLA one dance 4 4 22 1 SIA ft. SEAN PAUL cheap thrills 5 5 24 2 ALAN WALKER faded 6 6 16 3 FIFTH HARMONY ft. TY DOLLA $IGN work from home 7 7 33 4 MIKE POSNER i took a pill in ibiza 8 11 8 8 PINK just like fire 9 15 8 9 KUNGS vs. COOKIN' ON 3 BURNERS this girl 10 9 17 9 CHAINSMOKERS ft. DAYA don't let me down 11 8 34 8 DNCE cake by the ocean 12 17 4 12 DAVID GUETTA ft. ZARA LARSSON this one's for you 13 14 27 7 COLDPLAY ft. BEYONCÉ hymn for the weekend 14 10 36 4 LUKAS GRAHAM 7 years 15 18 10 15 GALANTIS no money 16 12 14 5 MEGHAN TRAINOR no 17 13 30 4 TWENTY ONE PILOTS stressed out 18 16 8 16 ENRIQUE IGLESIAS ft. WISIN duele el corazón 19 26 11 19 ADELE send my love (to your new lover) 20 19 25 7 JONAS BLUE ft. DAKOTA fast car 21 27 5 21 ARIANA GRANDE into you 22 20 20 1 RIHANNA ft. DRAKE work 23 24 11 20 DESIIGNER panda 24 22 31 1 JUSTIN BIEBER love yourself 25 30 15 20 TINIE TEMPAH ft. ZARA LARSSON girls like 26 29 5 26 DRAKE ft. -
Worldcharts TOP 200 Vom 15.08.2016
CHARTSSERVICE – WORLDCHARTS – TOP 200 NO. 869 – 15.08.2016 PL VW WO PK ARTIST SONG 1 2 4 1 MAJOR LAZER ft. JUSTIN BIEBER & MØ cold water 2 1 15 1 JUSTIN TIMBERLAKE can't stop the feeling! 3 3 16 1 CALVIN HARRIS ft. RIHANNA this is what you came for 4 4 17 3 KUNGS vs. COOKIN' ON 3 BURNERS this girl 5 7 10 5 SHAWN MENDES treat you better 6 5 19 1 DRAKE ft. WIZKID & KYLA one dance 7 6 31 1 SIA ft. SEAN PAUL cheap thrills 8 8 20 7 ADELE send my love (to your new lover) 9 13 9 9 JONAS BLUE ft. JP COOPER perfect strangers 10 11 26 7 CHAINSMOKERS ft. DAYA don't let me down 11 10 17 10 ENRIQUE IGLESIAS ft. WISIN duele el corazón 12 12 5 12 KATY PERRY rise 13 9 13 4 DAVID GUETTA ft. ZARA LARSSON this one's for you 14 15 14 11 ARIANA GRANDE into you 15 16 15 15 SELENA GOMEZ kill 'em with kindness 16 14 19 12 GALANTIS no money 17 19 10 17 KENT JONES don't mind 18 28 8 18 TWENTY ONE PILOTS heathens 19 17 17 15 TWENTY ONE PILOTS ride 20 26 5 20 BRITNEY SPEARS ft. G-EAZY make me… 21 24 29 21 CHARLIE PUTH ft. SELENA GOMEZ we don't talk anymore 22 20 14 20 DRAKE ft. RIHANNA too good 23 18 33 2 ALAN WALKER faded 24 22 13 15 ONEREPUBLIC wherever i go 25 23 36 7 COLDPLAY ft. -
Superstars Describe Why They're Appearing on Mda Labor Day Telethon
Contact: Jim Brown MDA Vice President – Public Relations 702-797-8535 (MDA Labor Day Telethon Office) or 520-903-8556 (cell) or [email protected] SUPERSTARS DESCRIBE WHY THEY’RE APPEARING ON MDA LABOR DAY TELETHON LAS VEGAS, Nev., Sept. 1, 2011 ― As the finishing touches are being finessed for the 46th annual Muscular Dystrophy Association Labor Day Telethon that will be broadcast nationwide from 6 p.m. to midnight in every U.S. time zone on Sunday, Sept. 4, mega star Celine Dion aptly described why the iconic show consistently attracts outstanding talent. “It’s always a privilege to be part of the MDA Labor Day Telethon,” said Celine, who’ll be performing in the 2011 Telethon’s opening hour. “I hope by taking part in this great cause, I can help MDA in its mission to make life better for families who are fighting muscle diseases. From supporting scientists who are searching for treatments and cures, to helping children go to MDA summer camp, MDA provides love and care in so many ways.” Celine’s motivation is shared by several artists who just confirmed their participation in Sunday’s primetime Telethon being broadcast by more than 150 television stations nationwide. For example, in a group message so typical of their harmonious sound, Boyz II Men members Shawn Stockton, Nathan and Wanya Morris said, "we’re excited to be part of the MDA Labor Day Telethon this year and lend our voices to a such a good cause. We remember watching it growing up and it's great to be a part of something so historic that benefits so many people everyday.