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Development Issues for Speech-Enabled Mobile Applications
Development Issues forSpeech-Enabled Mobile Applications Werner Kurschl, Stefan Mitsch, Rene Prokop and Johannes Schonb¨ ock¨ Research Center Hagenberg Upper Austria University of Applied Sciences Hauptstraße 117 A-4232 Hagenberg, AUSTRIA { werner.kurschl, stefan.mitsch, rene.prokop, johannes.schoenboeck} @fh-hagenberg.at Abstract: Developing aspeech-based application for mobile devices requires work upfront, since mobile devices and speech recognition systems vary dramatically in their capabilities. While mobile devices can concisely be classified by their processing power,memory,operating system and wireless network speed it is abit trickier for speech recognition engines. This paper presents acomprehensive approach that com- prises aprofound classification of speech recognition systems for mobile applications and aframework for mobile and distributed speech recognition. The framework called Gulliverspeeds up the development process with multi-modal components that can be easily used in aGUI designer and with abstraction layers that support the integration of various speech recognition engines depending on the user’sneeds. The framework itself provides the base for amodel-drivendevelopment approach. 1Introduction Developing speech-enabled applications for mobile devices typically requires comprehen- sive analysis of several speech processing engines and different architectural approaches before the desired application can be built. In addition, framework and tool support is often insufficient, which makes developing applications difficult: speech recognition sys- tems usually provide anative low-levelAPI or support Microsoft SAPI or Java SAPI (see [Mic] and [Sun98b]). Common to these APIs is that enhancing agraphical user interface with speech requires additional and separate speech input treatment based on amethod- call-interface; thus, the developer has to manually modify the speech recognition system’s state and handle textual results. -
Speech Technologies and Standards
Paolo Baggia Loquendo Speech Technologies and Standards DIT Seminars, Povo, Trento June 7th, 2006 © 2006 Loquendo SpA Loquendo Today Global company formed in 2001 as a spin-off from the Telecom Italia R&D center with over 30 years experience in Speech Technologies A Telecom Italia Group company HQ in Turin (Italy) and Sales offices in Miami (US), Madrid (Spain), Munich (Germany) and Paris (France), and a Worldwide Network of Agents. Market-leader in Italy, Spain, Greece with a strong presence in Europe, growing presence in North and Latin America Strategy:Strategy: “Best Innovation ¾¾ CompleteComplete set set of of speech speech technologies technologies on on aa wide wide spectrum spectrum of of devices devices in Multi-Lingual Speech Synthesis” Prize ¾¾ ReadyReady for for challenging challenging future future scenarios: scenarios: Multimodality,Multimodality, Security Security AVIOS-SpeechTEK West 2006 ¾¾ PartnershipPartnership as as a a key key factor factor © 2006 Loquendo SpA 2 Plan of my talk • The Past – Evolution of Speech Technologies (mainly ASR, TTS) – First Speech Applications (Touch Tones, IVRs) • The Present – The Impact of Standards – The (r)evolution of VoiceXML – A Constellation of W3C Standards – Work in progress • The Future – Voice and Video Applications – Speech and SemanticWeb – Towards Multimodality • Q&A © 2006 Loquendo SpA 3 A Brief History of Spoken Language Technology BL's Voder Von Kempelen's Dictation systems Spoken dialog Talking Machine Dictation Industry Industry Radio Rex Widespread use of MultiModal -
D2.2 - Final Prototypes and Final Report on the Perceptualization of Map Data, Context Sensing and Reasoning, and Hardware Design
SEVENTH FRAMEWORK PROGRAMME THEME 3 ICT - Information and Communication Technologies FP7 – ICT – 224675 HaptiMap Haptic, Audio and Visual Interfaces for Maps and Location Based Services Large-scale integrating project Challenge 7 - Independent living and inclusion D2.2 - Final prototypes and final report on the perceptualization of map data, context sensing and reasoning, and hardware design. Due date of deliverable: 30th April 2011 Original submission date: 29th April 2011 Revised version submission Date: 18th January 2012 Start date of project: 1st September 2008 Duration: M48 Lead contractor: UGLAS Project co-funded by the European Commission within the Seventh Framework Programme Dissemination Level PU Public PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services) HaptiMap, Deliverable D2.2 PU Final Prototypes Project Number FP7 – ICT – 224675 Project Title HaptiMap Haptic, Audio and Visual Interfaces for Maps and Location Based Services Document Type PU Document Number 1 Contractual date of delivery to the 30th April 2011 Commission Actual date of delivery to the Commission 29th April 2011 Resubmission date of delivery to 19th January 2012 Commission Title of the Document D2.1 - Final prototypes and final report on the perceptualization of map data, context sensing and reasoning, and hardware design Work package contributing 2 Nature of the Document RE Abstract This document outlines final prototypes and hardware development for WP2. Keyword list System Prototyping 3 HaptiMap Consortium – www.haptimap.org FP7-ICT- 224675 HaptiMap, Deliverable D2.2 PU Final Prototypes Function Name Partner Editors David McGookin UGLAS L. -
Spoken Dialogue Systems: Architectures and Applications
Spoken Dialogue Systems: Architectures and Applications Doctoral Thesis Javier Mikel Olaso Fernandez Advisor María Inés Torres Barañano Leioa 2017 (cc)2017 JAVIER MIKEL OLANO FERNANDEZ (cc by-nc 4.0) Contents List of Figures ................................ v List of Tables ................................. vii List of Symbols ............................... ix 1 Introduction ............................... 1 2 Spoken Dialogue Systems ....................... 5 1 Overview . 5 2 Components of a Spoken Dialogue System . 6 2.1 Automatic Speech Recognition . 7 2.2 Natural Language Understanding . 8 2.3 Natural Language Generation . 9 2.4 Text-To-Speech Synthesis . 9 2.5 Dialogue Management . 10 2.5.1 State-Based . 10 2.5.1.1 Finite State-Based . 11 2.5.1.2 Frame-Based . 12 2.5.2 Agent-Based . 13 2.5.3 Information State-Based . 14 2.5.4 Statistical . 14 2.5.4.1 MDP and POMDP . 15 2.5.4.2 Stochastic Finite State Bi-Automata . 18 2.5.4.3 Neural Networks . 22 2.6 Other Components . 22 3 Examples of Spoken Dialogue Systems . 23 3 Frameworks and Toolkits ........................ 25 1 PC under Windows OS . 25 2 PC under Unix-like OS . 28 3 PC under Windows or Unix-like OS . 28 4 Other Platforms . 31 4 Preliminary Systems ........................... 35 1 Introduction . 35 2 INMA . 35 2.1 Architecture . 36 2.2 Configuring and Launching the System . 38 2.3 Modules Implementation Details . 40 2.3.1 Automatic Speech Recognition and Text to Speech . 40 2.3.2 User Interface . 41 2.3.3 Data Backend . 42 ii Contents 2.3.4 Comprehension . 44 3 RTMIVA . 45 3.1 Architecture Definition . -
Subject 504026
TEACHING GUIDE 2017/18 Centre 345 - Faculty of Engineering - Bilbao Cycle Indiferente Plan INTEL902 - Master in Telecommunication Engineering Year Second year SUBJECT 504026 - Speech Technologies ECTS Credits: 4,5 DESCRIPTION & CONTEXTUALISATION OF THE SUBJECT The subject is a general introduction to speech technologies and its goal is to qualify the student to work in this area. This includes both the research profiles and the professional profiles devoted to the design, development and commercialization of dialogue, speech synthesis and recognition systems, biometric security systems, etc. In this subject, basic concepts of signal processing taught in the in the Telecommunication Technology Engineering degree, mainly in the subject of Signal Treatment and also in Multimedia Signal Processing, where basic techniques to process audio and speech signals are studied. Besides, knowledge in advanced signal statistical processing is required. This topic is studied in Advanced Signal Processing, in the first course of the master. COMPETENCIES/LEARNING RESULTS FOR THE SUBJECT COMPETENCIAS DE LA ASIGNATURA Conocer las estrategias fundamentales empleadas en los sistemas de síntesis y de codificación de la señal de voz, manejando las herramientas informáticas básicas para el procesado y tratamiento de la señal de voz. Conocer e interpretar los procesos de generación y percepción de la voz humana. Comprender la terminología empleada en el campo del tratamiento de la señal de voz, de forma que sea capaz de interpretar un trabajo de investigación descrito en una revista Comprender e interpretar los principales parámetros utilizados en la representación de la señal de voz RESULTADOS DE APRENDIZAJE DE LA ASIGNATURA THEORETICAL/PRACTICAL CONTENT Lesson 1 Introduction to speech technologies. -
Mobile Speech: Unlocking Personal Apps, Features and Functions
Mobile Speech: Unlocking Personal Apps, Features and Functions The forces of human nature, technological progress and regulatory stricture are converging to boost interest in “truly hands-free” mobile applications. Dozens of firms have responded with a broad variety of software, services and features that work remarkably well. Next step: to build a sustainable market model. September 2009 Dan Miller Sr. Analyst Opus Research, Inc. 300 Brannan St., Suite 305 San Francisco, CA 94107 For sales inquires please e-mail [email protected] or call +1(415)904-7666 This report shall be used solely for internal information purposes. Reproduction of this report without prior written permission is forbidden. Access to this report is limited to the license terms agreed to originally and any changes must be agreed upon in writing. The information contained herein has been obtained from sources believe to be reliable. However, Opus Research, Inc. accepts no responsibility whatsoever for the content or legality of the report. Opus Research, Inc. disclaims all warranties as to the accuracy, completeness or adequacy of such information. Further, Opus Research, Inc. shall have no liability for errors, omissions or inadequacies in the information contained herein or interpretations thereof. The opinions expressed herein may not necessarily coincide with the opinions and viewpoints of Opus Research, Inc. and are subject to change without notice. Published September 2009 © Opus Research, Inc. All rights reserved. Mobile Speech: Unlocking Personal Apps, Functions & Features Page ii Key Findings: • Voice control of mobile services has made great strides – A common theme in our research this year is that “the technology works!” and makes for a much-improved user experience.