HMM .075 x .075 HYPERBOLOID SERIES HYPERBOLOID CONNECTORS FOR SUPERIOR PERFORMANCE IN ALL APPLICATIONS IEH

Source URL: www.iehcorp.com

PARTICLE-BASED TRACKING MODEL FOR AUTOMATIC ANOMALY DETECTION Erwan Jouneau and Cyril Carincotte Multitel asbl - 2 Rue Pierre et Marie CurieMons - Belgium ABSTRACT In this paper, we present a new method to automa

Source URL: www.multitel.be

• Science
• Artificial intelligence
• Anomaly
• HMM
• Activity recognition
• Statistics
• Bioinformatics
• Hidden Markov model

WORD-LEVEL EMPHASIS MODELLING IN HMM-BASED SPEECH SYNTHESIS K. Yu, F. Mairesse and S. Young Cambridge University Engineering Department, Trumpington Street, Cambridge, CB2 1PZ, UK Email: {ky219, f.mairesse, sjy}@eng.cam.

Source URL: mi.eng.cam.ac.uk

• Artificial intelligence applications
• Assistive technology
• Speech synthesis
• Natural language processing
• Artificial intelligence
• Tree
• Word-sense disambiguation
• Computational linguistics
• Linguistics
• Science

GOING TO A PIZZA PARTY JOHN WHERE ARE YOU GOING? Pizza party. Going to a pizza party. Hmm, going to a pizza party. JOHN NOW WHERE ARE YOU GOING TO THIS PIZZA PARTY? WHO INVITED YOU TO A PIZZA PARTY?

Source URL: www.denisetassin.com

• Pizza
• Feed the Birds
• Bird
• Feed
• Food and drink
• Cuisine
• Italian cuisine

PROBABLISTIC MODELLING OF F0 IN UNVOICED REGIONS IN HMM BASED SPEECH SYNTHESIS K. Yu, T. Toda∗ , M. Gasic, S. Keizer, F. Mairesse, B. Thomson and S. Young Cambridge University Engineering Department, Trumpington Street

Source URL: mi.eng.cam.ac.uk

• Linguistics
• Hidden Markov model
• Phonetics
• Accessibility
• Speech recognition
• Speech synthesis
• Source–filter model of speech production
• Voice
• Computational linguistics
• Science
• Bioinformatics

F-HMM_LACorp-Asian_Fall2014.indd

Source URL: www.huntington.org

• World Heritage Sites in Italy
• Ancient cities
• Landscape artists
• Osci
• Campanian volcanic arc
• Mount Vesuvius
• Naples
• Joseph Wright of Derby
• Pompeii
• Campania
• Volcanology
• Geology

Glottal Source and Prosodic Prominence Modelling in HMM-based Speech Synthesis for the Blizzard Challenge 2009 J. Sebastian Andersson, Joao P. Cabral, Leonardo Badino, Junichi Yamagishi, Robert A.J. Clark The Centre for

Source URL: www.cstr.ed.ac.uk

• Tone
• Assistive technology
• Speech synthesis
• Pitch accent
• Speech recognition
• Linguistics
• Hidden Markov model
• Human–computer interaction
• International Phonetic Alphabet
• Computational linguistics
• Science
• Computer accessibility

8th ISCA Speech Synthesis Workshop • August 31 – September 2, 2013 • Barcelona, Spain Noise Robustness in HMM-TTS Speaker Adaptation Kayoko Yanagisawa, Javier Latorre, Vincent Wan, Mark J. F. Gales and Simon King

Source URL: www.cstr.ed.ac.uk

• Automatic identification and data capture
• Speech processing
• Speech recognition
• Artificial intelligence applications
• Human communication
• Speech synthesis
• Speech Translation
• Speech enhancement
• Computational linguistics
• Science
• Human–computer interaction

IMPROVING INTELLIGIBILITY IN NOISE OF HMM-GENERATED SPEECH VIA NOISE-DEPENDENT AND -INDEPENDENT METHODS Cassia Valentini-Botinhao1 , Elizabeth Godoy2 , Yannis Stylianou2 , Bastian Sauert3 Simon King1 and Junichi Yamagish

Source URL: www.cstr.ed.ac.uk

• Communication
• Hearing
• Science
• Technology
• Human voice
• Speech enhancement
• Speech synthesis
• Speech recognition
• Cepstral
• Waves
• Computational linguistics
• Sound

8th ISCA Speech Synthesis Workshop • August 31 – September 2, 2013 • Barcelona, Spain Investigating the shortcomings of HMM synthesis Thomas Merritt, Simon King The Centre for Speech Technology Research, The Unive

Source URL: www.cstr.ed.ac.uk

• Summary statistics
• Probability theory
• Variance
• Hidden Markov model
• Speech synthesis
• Standard deviation
• Estimation theory
• Multidimensional scaling
• Degrees of freedom
• Statistics
• Data analysis
• Computational linguistics