'Speech recognition' diaporamas de présentation

Search and Decoding in Speech Recognition

Search and Decoding in Speech Recognition. Automatic Speech Recognition. Automatic Speech Recognition. Spoken language understanding is a difficult task, and it is remarkable that humans do well at it.

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Deep Learning from Speech Analysis/Recognition to Language/Multimodal Processing

Deep Learning from Speech Analysis/Recognition to Language/Multimodal Processing. Li Deng Deep Learning Technology Center, Microsoft Research, Redmond, WA. USA A Tutorial at Intern. Workshop on Mathematical Issues in Information Sciences (MIIS). Outline.

1.65k views • 125 slides

Assistive Technology Basics Teresa Goddard Lisa Mathess (800) 526-7234 (Voice)

Assistive Technology Basics Teresa Goddard Lisa Mathess (800) 526-7234 (Voice) (877) 781-9403 (TTY) jan@askjan.org. Assistive Technology. What is Assistive Technology?

743 views • 49 slides

Automatic Speech Recognition: An Overview

Automatic Speech Recognition: An Overview. Julia Hirschberg CS 4706 (Thanks to Roberto Pieraccini and Francis Ganong for some slides). DIALOG. SEMANTICS. SPEECH RECOGNITION. SPOKEN LANGUAGE UNDERSTANDING. SYNTAX. LEXICON. MORPHOLOGY. SPEECH SYNTHESIS. PHONETICS. DIALOG

608 views • 43 slides

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MODELLING LATVIAN LANGUAGE FOR AUTOMATIC SPEECH RECOGNITION

MODELLING LATVIAN LANGUAGE FOR AUTOMATIC SPEECH RECOGNITION. Askars Salimbajevs. Supervisor: Prof. Inguna Skadi?a University of Latvia. Introduction Acoustic modelling Automatic data acquisition Pronunciation model Language modelling Text preprocessing Word and sub-word N-gram models

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Mobile Dictation With Automatic Speech Recognition for Healthcare Purposes

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Reproducible Computational Experiments

Reproducible Computational Experiments. Mark Liberman University of Pennsylvania http://ling.upenn.edu/~myl. Reproducible (?) Replicable Computational Experiments. Mark Liberman University of Pennsylvania http://ling.upenn.edu/~myl.

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BY: PRATIBHA CHANNAMSETTY SHRUTHI SAMBASIVAN

SPEECH RECOGNITION FOR MOBILE SYSTEMS. BY: PRATIBHA CHANNAMSETTY SHRUTHI SAMBASIVAN. Introduction. What is speech recognition? Automatic speech recognition(ASR) is the process by which a computer maps an acoustic speech signal to text. CLASSIFICATION OF SPEECH RECOGNITION SYSTEM. U sers

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Mark Hasegawa-Johnson January 29, 2003

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Speech Recognition

Speech Recognition. Part 3 Back end processing. Speech recognition simplified block diagram. Training. Speech Capture. Feature Extraction. Models. Pattern Matching. Process Results. Text. Building a phone model. Annotate the speech input. Split and create feature vectors for each.

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Ruang Lingkup Mengapa dan Apa Siapa Saja yang Terlibat Konsep dan Dasar Sejarah dan Paradigma IMK

PENDAHULUAN. Ruang Lingkup Mengapa dan Apa Siapa Saja yang Terlibat Konsep dan Dasar Sejarah dan Paradigma IMK. Course Overview. Human abilities Evaluation (without users) Design Dialog & interaction Evaluation (with users) Special topics CSCW, InfoVis, Ubicomp, Agents.

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NONLINEAR DYNAMIC INVARIANTS FOR CONTINUOUS SPEECH RECOGNITION

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Improvement in the quality of automated dictation by making explicit use of semantic knowledge

Improvement in the quality of automated dictation by making explicit use of semantic knowledge. Klaus Stanglmayr Friday, February 23, 2007. Philips Speech Recognition Systems. Philips Speech Recognition Systems. A business unit of Royal Philips Electronics

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Speech Recognition

Speech Recognition. UNIT -5. Introduction. After years of research and development the accuracy of automatic speech recognition remains one of the important research challenges ( eg ., variations of the context, speakers, and environment ).

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Natural Language Processing (NLP)

Natural Language Processing (NLP). Prof. Carolina Ruiz Computer Science WPI. References. The essence of Artificial Intelligence By A. Cawsey Prentice Hall Europe 1998 Artificial Intelligence: Theory and Practice By T. Dean, J. Allen, and Y. Aloimonos.

626 views • 19 slides

Overview of Statistical Language Models

Overview of Statistical Language Models. ChengXiang Zhai Department of Computer Science University of Illinois, Urbana-Champaign. Outline. What is a statistical language model (SLM)? Brief history of SLM Types of SLM Applications of SLM. What is a Statistical Language Model (LM)?.

682 views • 18 slides

Probabilistic reasoning over time

Probabilistic reasoning over time. This sentence is likely to be untrue in the future!. The basic problem. What do we know about the state of the world now given a history of the world before . The only evidence we have are probabilities.

327 views • 15 slides

Anniversary Conference and Workshop Summary

Anniversary Conference and Workshop Summary. PACS. DICOM services supporting PACS Realities of deploying DICOM in a PACS Transport between PACS Internationalization challenges. Expanding Modality Coverage. Widely accepted Radiology Cardiology Radiotherapy

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