Speech Synthesis 1 Speech Synthesis
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Weeel for the IBM 704 Data Processing System Reference Manual
aC sicru titi Wane: T| weeel for the IBM 704 Data Processing System Reference Manual FORTRAN II for the IBM 704 Data Processing System © 1958 by International Business Machines Corporation MINOR REVISION This edition, C28-6000-2, is a minor revision of the previous edition, C28-6000-1, but does not obsolete it or C28-6000. The principal change is the substitution of a new discussion of the COMMONstatement. TABLE OF CONTENTS Page General Introduction... ee 1 Note on Associated Publications Le 6 PART |. THE FORTRAN If LANGUAGE , 7 Chapter 1. General Properties of a FORTRAN II Source Program . 9 Types of Statements. 1... 1. ee ee ee we 9 Types of Source Programs. .......... ~ ee 9 Preparation of Input to FORTRAN I Translatorcee es 9 Classification of the New FORTRAN II Statements. 9 Chapter 2. Arithmetic Statements Involving Functions. ....... 10 Arithmetic Statements. .. 1... 2... ew eee . 10 Types of Functions . il Function Names. ..... 12 Additional Examples . 13 Chapter 3. The New FORTRAN II Statements ......... 2 16 CALL .. 16 SUBROUTINE. 2... 6 ee ee te ew eh ee es 17 FUNCTION. 2... 1 ee ee ww ew ew ww ew ew ee 18 COMMON ...... 2. ee se ee eee wee . 20 RETURN. 2... 1 1 ew ee te ee we wt wt wh wt 22 END... «4... ee we ee ce ew oe te tw . 22 PART Il, PRIMER ON THE NEW FORTRAN II FACILITIES . .....0+2«~W~ 25 Chapter 1. FORTRAN II Function Subprograms. 0... eee 27 Purpose of Function Subprograms. .....445... 27 Example 1: Function of an Array. ....... 2 + 6 27 Dummy Variables. -
Spring 2018 Undergraduate Law Journal
SPRING 2018 UNDERGRADUATE LAW JOURNAL The Final Frontier: Evolution of Space Law in a Global Society By: Garett Faulkender and Stephan Schneider Introduction “Space: the final frontier!” These are the famous introductory words spoken by William Shatner on every episode of Star Trek. This science-fiction TV show has gained a cult-following with its premise as a futuristic Space odyssey. Originally released in 1966, many saw the portrayed future filled with Space-travel, inter-planetary commerce and politics, and futuristic technology as merely a dream. However, today we are starting to explore this frontier. “We are entering an exciting era in [S]pace where we expect more advances in the next few decades than throughout human history.”1 Bank of America/Merrill Lynch has predicted that the Space industry will grow to over $2.7 trillion over the next three decades. Its report said, “a new raft of drivers is pushing the ‘Space Age 2.0’”.2 Indeed, this market has seen start-up investments in the range of $16 billion,3 helping fund impressive new companies like Virgin Galactic and SpaceX. There is certainly a market as Virgin Galactic says more than 600 customers have registered for a $250,000 suborbital trip, including Leonardo DiCaprio, Katy Perry, Ashton Kutcher, and physicist Stephen Hawking.4 Although Space-tourism is the exciting face of a future in Space, the Space industry has far more to offer. According to the Satellite Industries 1 Michael Sheetz, The Space Industry Will Be Worth Nearly $3 Trillion in 30 Years, Bank of America Predicts, CNBC, (last updated Oct. -
THE DEVELOPMENT of ACCENTED ENGLISH SYNTHETIC VOICES By
THE DEVELOPMENT OF ACCENTED ENGLISH SYNTHETIC VOICES by PROMISE TSHEPISO MALATJI DISSERTATION Submitted in fulfilment of the requirements for the degree of MASTER OF SCIENCE in COMPUTER SCIENCE in the FACULTY OF SCIENCE AND AGRICULTURE (School of Mathematical and Computer Sciences) at the UNIVERSITY OF LIMPOPO SUPERVISOR: Mr MJD Manamela CO-SUPERVISOR: Dr TI Modipa 2019 DEDICATION In memory of my grandparents, Cecilia Khumalo and Alfred Mashele, who always believed in me! ii DECLARATION I declare that THE DEVELOPMENT OF ACCENTED ENGLISH SYNTHETIC VOICES is my own work and that all the sources that I have used or quoted have been indicated and acknowledged by means of complete references and that this work has not been submitted before for any other degree at any other institution. ______________________ ___________ Signature Date iii ACKNOWLEDGEMENTS I want to recognise the following people for their individual contributions to this dissertation: • My brother, Mr B.I. Khumalo and the whole family for the unconditional love, support and understanding. • A distinct thank you to both my supervisors, Mr M.J.D. Manamela and Dr T.I. Modipa, for their guidance, motivation, and support. • The Telkom Centre of Excellence for Speech Technology for providing the resources and support to make this study a success. • My colleagues in Department of Computer Science, Messrs V.R. Baloyi and L.M. Kola, for always motivating me. • A special thank you to Mr T.J. Sefara for taking his time to participate in the study. • The six Computer Science undergraduate students who sacrificed their precious time to participate in data collection. -
La Voz Humana
UNIVERSIDAD DE CHILE FACULTAD DE ARTES MAGISTER EN ARTES MEDIALES SHOUT! Tesis para optar al Grado de Magíster en Artes Medialess ALUMNO: Christian Oyarzún Roa PROFESOR GUÍA: Néstor Olhagaray Llanos Santiago, Chile 2012 A los que ya no tienen voz, a los viejos, a los antiguos, a aquellos que el silencio se lleva en la noche. ii AGRADECIMIENTOS Antes que nada quiero agradecer a Néstor Olhagaray, por el tesón en haberse mantenido como profesor guía de este proyecto y por la confianza manifestada más allá de mis infinitos loops y procastinación. También quisiera manifestar mis agradecimientos a Álvaro Sylleros quién, como profesor del Diplomado en Lutería Electrónica en la PUC, estimuló y ayudó a dar forma a parte sustancial de lo aquí expuesto. A Valentina Montero por la ayuda, referencia y asistencia curatorial permanente, A Pablo Retamal, Pía Sommer, Mónica Bate, Marco Aviléz, Francisco Flores, Pablo Castillo, Willy MC, Álvaro Ceppi, Valentina Serrati, Yto Aranda, Leonardo Beltrán, Daniel Tirado y a todos aquellos que olvido y que participaron como informantes clave, usuarios de prueba ó simplemente apoyando entusiastamente el proyecto. Finalmente, quiero agradecer a Claudia González, quien ha sido una figura clave dentro de todo este proceso. Gracias Clau por tu sentido crítico, por tu presencia inspiradora y la ejemplar dedicación y amor por lo que haces. iii Tabla de Contenidos RESÚMEN v INTRODUCCIÓN 1 A Hard Place 1 Descripción 4 Objetivos 6 LA VOZ HUMANA 7 La voz y el habla 7 Balbuceos, risas y gritos 11 Yo no canto por cantar 13 -
Rečové Interaktívne Komunikačné Systémy
Rečové interaktívne komunikačné systémy Matúš Pleva, Stanislav Ondáš, Jozef Juhár, Ján Staš, Daniel Hládek, Martin Lojka, Peter Viszlay Ing. Matúš Pleva, PhD. Katedra elektroniky a multimediálnych telekomunikácií Fakulta elektrotechniky a informatiky Technická univerzita v Košiciach Letná 9, 04200 Košice [email protected] Táto učebnica vznikla s podporou Ministerstvo školstva, vedy, výskumu a športu SR v rámci projektu KEGA 055TUKE-04/2016. c Košice 2017 Názov: Rečové interaktívne komunikačné systémy Autori: Ing. Matúš Pleva, PhD., Ing. Stanislav Ondáš, PhD., prof. Ing. Jozef Juhár, CSc., Ing. Ján Staš, PhD., Ing. Daniel Hládek, PhD., Ing. Martin Lojka, PhD., Ing. Peter Viszlay, PhD. Vydal: Technická univerzita v Košiciach Vydanie: prvé Všetky práva vyhradené. Rukopis neprešiel jazykovou úpravou. ISBN 978-80-553-2661-0 Obsah Zoznam obrázkov ix Zoznam tabuliek xii 1 Úvod 14 1.1 Rečové dialógové systémy . 16 1.2 Multimodálne interaktívne systémy . 19 1.3 Aplikácie rečových interaktívnych komunikačných systémov . 19 2 Multimodalita a mobilita v interaktívnych systémoch s rečo- vým rozhraním 27 2.1 Multimodalita . 27 2.2 Mobilita . 30 2.3 Rečový dialógový systém pre mobilné zariadenia s podporou multimodality . 31 2.3.1 Univerzálne riešenia pre mobilné terminály . 32 2.3.2 Projekt MOBILTEL . 35 3 Parametrizácia rečových a audio signálov 40 3.1 Predspracovanie . 40 3.1.1 Preemfáza . 40 3.1.2 Segmentácia . 41 3.1.3 Váhovanie oknovou funkciou . 41 3.2 Spracovanie rečového signálu v spektrálnej oblasti . 41 3.2.1 Lineárna predikčná analýza . 43 3.2.2 Percepčná Lineárna Predikčná analýza . 43 3.2.3 RASTA metóda . 43 3.2.4 MVDR analýza . -
Aac 2, 3, 4, 5, 6, 50, 51, 52, 53, 55, 56, 57, 58, 59, 60, 61, 62
315 Index A augmentative and alternative communication (AAC) 130, 145, 148 AAC 2, 3, 4, 5, 6, 50, 51, 52, 53, 55, 56, 57, Augmentative and Alternative Communication 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, (AAC) 50 69, 130, 131, 138, 140, 141, 142, 143, augmented speech 116, 126 144, 145, 147, 148, 149, 150, 153, 156, Augmented Speech Communication 117 158, 159, 160, 161, 162, 163, 164, 165, Augmented speech communication (ASC) 116 172, 173, 174, 175, 192, 194, 198, 205, automatic categorization 220 206, 207, 208, 213, 214, 215, 216, 257, automatic speech recognition 100 258, 259, 260, 263, 265 Automatic Speech Recognition (ASR) 189 able-bodied people 220 accessibility 12, 14, 15, 21 B acoustic energy 31 adaptive differential pulse code modulation background noise 56, 67, 130, 132, 134, 135, (ADPCM) 32 136, 137, 141, 142, 144 AIBO 17 BCI 17 aided communication techniques 205 bit rate 31, 32, 33, 41, 45, 47 aided communicator 234, 235, 241, 243, 245, bits per second (bps) 31 248, 250, 252 Blissymbols 235, 238, 239, 240, 241, 242, 243, aided language development 235 244, 246, 247, 250, 256 allophones 34, 35 brain-computer interfaces (BCI) 17 alternate reader 17 Brain Computer Interfaces (BCI’s) 6 alternative and augmentative communication brain-machine interface (BMI) 17 (AAC) 2, 93 C alternative communication 1 amyotrophic lateral sclerosis (ALS) 1 CALL 189, 190, 191, 192, 193, 196, 198, 199, analog-to-digital converter 30, 31 201, 202, 203 anti-aliasing (low-pass) filters 3 1 CASLT 188, 189, 190, 191, 193, 198, 199 aphasia 148, 149, -
Commercial Tools in Speech Synthesis Technology
International Journal of Research in Engineering, Science and Management 320 Volume-2, Issue-12, December-2019 www.ijresm.com | ISSN (Online): 2581-5792 Commercial Tools in Speech Synthesis Technology D. Nagaraju1, R. J. Ramasree2, K. Kishore3, K. Vamsi Krishna4, R. Sujana5 1Associate Professor, Dept. of Computer Science, Audisankara College of Engg. and Technology, Gudur, India 2Professor, Dept. of Computer Science, Rastriya Sanskrit VidyaPeet, Tirupati, India 3,4,5UG Student, Dept. of Computer Science, Audisankara College of Engg. and Technology, Gudur, India Abstract: This is a study paper planned to a new system phonetic and prosodic information. These two phases are emotional speech system for Telugu (ESST). The main objective of usually called as high- and low-level synthesis. The input text this paper is to map the situation of today's speech synthesis might be for example data from a word processor, standard technology and to focus on potential methods for the future. ASCII from e-mail, a mobile text-message, or scanned text Usually literature and articles in the area are focused on a single method or single synthesizer or the very limited range of the from a newspaper. The character string is then preprocessed and technology. In this paper the whole speech synthesis area with as analyzed into phonetic representation which is usually a string many methods, techniques, applications, and products as possible of phonemes with some additional information for correct is under investigation. Unfortunately, this leads to a situation intonation, duration, and stress. Speech sound is finally where in some cases very detailed information may not be given generated with the low-level synthesizer by the information here, but may be found in given references. -
Models of Speech Synthesis ROLF CARLSON Department of Speech Communication and Music Acoustics, Royal Institute of Technology, S-100 44 Stockholm, Sweden
Proc. Natl. Acad. Sci. USA Vol. 92, pp. 9932-9937, October 1995 Colloquium Paper This paper was presented at a colloquium entitled "Human-Machine Communication by Voice," organized by Lawrence R. Rabiner, held by the National Academy of Sciences at The Arnold and Mabel Beckman Center in Irvine, CA, February 8-9,1993. Models of speech synthesis ROLF CARLSON Department of Speech Communication and Music Acoustics, Royal Institute of Technology, S-100 44 Stockholm, Sweden ABSTRACT The term "speech synthesis" has been used need large amounts of speech data. Models working close to for diverse technical approaches. In this paper, some of the the waveform are now typically making use of increased unit approaches used to generate synthetic speech in a text-to- sizes while still modeling prosody by rule. In the middle of the speech system are reviewed, and some of the basic motivations scale, "formant synthesis" is moving toward the articulatory for choosing one method over another are discussed. It is models by looking for "higher-level parameters" or to larger important to keep in mind, however, that speech synthesis prestored units. Articulatory synthesis, hampered by lack of models are needed not just for speech generation but to help data, still has some way to go but is yielding improved quality, us understand how speech is created, or even how articulation due mostly to advanced analysis-synthesis techniques. can explain language structure. General issues such as the synthesis of different voices, accents, and multiple languages Flexibility and Technical Dimensions are discussed as special challenges facing the speech synthesis community. -
Estudios De I+D+I
ESTUDIOS DE I+D+I Número 51 Proyecto SIRAU. Servicio de gestión de información remota para las actividades de la vida diaria adaptable a usuario Autor/es: Catalá Mallofré, Andreu Filiación: Universidad Politécnica de Cataluña Contacto: Fecha: 2006 Para citar este documento: CATALÁ MALLOFRÉ, Andreu (Convocatoria 2006). “Proyecto SIRAU. Servicio de gestión de información remota para las actividades de la vida diaria adaptable a usuario”. Madrid. Estudios de I+D+I, nº 51. [Fecha de publicación: 03/05/2010]. <http://www.imsersomayores.csic.es/documentos/documentos/imserso-estudiosidi-51.pdf> Una iniciativa del IMSERSO y del CSIC © 2003 Portal Mayores http://www.imsersomayores.csic.es Resumen Este proyecto se enmarca dentro de una de las líneas de investigación del Centro de Estudios Tecnológicos para Personas con Dependencia (CETDP – UPC) de la Universidad Politécnica de Cataluña que se dedica a desarrollar soluciones tecnológicas para mejorar la calidad de vida de las personas con discapacidad. Se pretende aprovechar el gran avance que representan las nuevas tecnologías de identificación con radiofrecuencia (RFID), para su aplicación como sistema de apoyo a personas con déficit de distinta índole. En principio estaba pensado para personas con discapacidad visual, pero su uso es fácilmente extensible a personas con problemas de comprensión y memoria, o cualquier tipo de déficit cognitivo. La idea consiste en ofrecer la posibilidad de reconocer electrónicamente los objetos de la vida diaria, y que un sistema pueda presentar la información asociada mediante un canal verbal. Consta de un terminal portátil equipado con un trasmisor de corto alcance. Cuando el usuario acerca este terminal a un objeto o viceversa, lo identifica y ofrece información complementaria mediante un mensaje oral. -
Magic Quadrant for Interactive Voice Response Systems and Enterprise Voice Portals, 2008
Magic Quadrant for Interactive Voice Response Systems and Enterprise Voice Portals, 2008 Gartner RAS Core Research Note G00154201, Steve Cramoysan, Rich Costello, 18 February 2008 RA1 05192008 Organizations are increasingly adopting voice response solutions based on Internet standards and a voice portal architecture. Leading vendors are improving integration between voice self-service and live-agent functions, and reducing the complexity of developing and operating solutionOrganizations are increasingly adopting voice response solutions based on Internet standards and a voice portal architecture. Leading vendors are improving integration between voice self-service and live-agent functions, and reducing the complexity of developing and operating solutions. WHAT YOU NEED TO KNOW Providing self-service functionality is an important strategy that will help call center managers balance costs and quality of service. Leading companies require their customer service operations to provide increased automation and smooth integration from automated self- service to live-agent-handled tasks. They also need tighter integration between channels, and the ability to respond to the fast-changing application needs of the call center business. These business drivers are, in turn, leading to greater use of speech recognition and a shift to standards-based platforms and Web-based architectures for voice portals. They are also increasing the need for improved tools to enable call center staff to reconfigure applications without the help of technical staff. Functional differences between vendor platform products will erode, and vendor consolidation will continue. Differentiation will be based more often on integration in two directions. First, voice response is becoming a part of the call center portfolio, with the routing function and voice response increasingly being sourced and integrated by the same vendor. -
Expression Control in Singing Voice Synthesis
Expression Control in Singing Voice Synthesis Features, approaches, n the context of singing voice synthesis, expression control manipu- [ lates a set of voice features related to a particular emotion, style, or evaluation, and challenges singer. Also known as performance modeling, it has been ] approached from different perspectives and for different purposes, and different projects have shown a wide extent of applicability. The Iaim of this article is to provide an overview of approaches to expression control in singing voice synthesis. We introduce some musical applica- tions that use singing voice synthesis techniques to justify the need for Martí Umbert, Jordi Bonada, [ an accurate control of expression. Then, expression is defined and Masataka Goto, Tomoyasu Nakano, related to speech and instrument performance modeling. Next, we pres- ent the commonly studied set of voice parameters that can change and Johan Sundberg] Digital Object Identifier 10.1109/MSP.2015.2424572 Date of publication: 13 October 2015 IMAGE LICENSED BY INGRAM PUBLISHING 1053-5888/15©2015IEEE IEEE SIGNAL PROCESSING MAGAZINE [55] noVEMBER 2015 voices that are difficult to produce naturally (e.g., castrati). [TABLE 1] RESEARCH PROJECTS USING SINGING VOICE SYNTHESIS TECHNOLOGIES. More examples can be found with pedagogical purposes or as tools to identify perceptually relevant voice properties [3]. Project WEBSITE These applications of the so-called music information CANTOR HTTP://WWW.VIRSYN.DE research field may have a great impact on the way we inter- CANTOR DIGITALIS HTTPS://CANTORDIGITALIS.LIMSI.FR/ act with music [4]. Examples of research projects using sing- CHANTER HTTPS://CHANTER.LIMSI.FR ing voice synthesis technologies are listed in Table 1. -
UN SYNTHÉTISEUR DE LA VOIX CHANTÉE BASÉ SUR MBROLA POUR LE MANDARIN Liu Ning
UN SYNTHÉTISEUR DE LA VOIX CHANTÉE BASÉ SUR MBROLA POUR LE MANDARIN Liu Ning To cite this version: Liu Ning. UN SYNTHÉTISEUR DE LA VOIX CHANTÉE BASÉ SUR MBROLA POUR LE MAN- DARIN. Journées d’Informatique Musicale, 2012, Mons, France. hal-03041805 HAL Id: hal-03041805 https://hal.archives-ouvertes.fr/hal-03041805 Submitted on 5 Dec 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. Actes des Journées d’Informatique Musicale (JIM 2012), Mons, Belgique, 9-11 mai 2012 UN SYNTHÉTISEUR DE LA VOIX CHANTÉE BASÉ SUR MBROLA POUR LE MANDARIN Liu Ning CICM (Centre de recherche en Informatique et Création Musicale) Université Paris VIII, MSH Paris Nord [email protected] RESUME fonction de la mélodie et des paroles à partir d’un fichier MIDI [7]. Dans cet article, nous présentons le projet de développement d’un synthétiseur de la voix chantée basé Néanmoins, les synthèses de la voix chantée pour la sur MBROLA en mandarin pour la langue chinoise. langue chinoise ont encore des limites techniques. Par Notre objectif vise à développer un synthétiseur qui exemple, le système à partir de la lecture de fichier MIDI puisse fonctionner en temps réel, qui soit capable de se est un système en temps différé.