PPT-1 Automatic Speech Recognition: An Overview

Julia Hirschberg CS 4706 Thanks to Roberto Pieraccini and Francis Ganong for some slides 2 Recreating the Speech Chain DIALOG SEMANTICS SYNTAX LEXICON MORPHOLOGY PHONETICS VOCALTRACT. within . Noisy Environments. .. Florian . Bacher. & Christophe Sourisse. [623.400] Seminar in Interactive Systems. Agenda. Introduction. Methodology. Experiment Description. Implementation. Results. Julia Hirschberg. COMS . 4706. (Thanks to Josh Gordon for slides.). 1. SDS Architectures. Software abstractions that . coordinate . the NLP components required for human-computer dialogue. Conduct task-oriented, limited-domain conversations . Tomer. . Meshorer. Agenda. This presentation describes the use of speech recognition for:. . HCI . for spastic . dysarthria. patients . [M. Hasegawa-Johnson]. Identify progression of . P. arkinson disease using speech signal[A. in Speech Recognition. Author. ：. Mark . Gales. 1. and Steve . Young. 2. Published. ：. 21 . Feb . 2008. . . Subjects. ：. Speech/audio/image/video . compression. Outline. Introduction. Architecture of an HMM-Based . 1. Speech Recognition and HMM Learning. Overview of speech recognition approaches. Standard Bayesian Model. Features. Acoustic Model Approaches. Language Model. Decoder. Issues. Hidden Markov Models. Spoken Language Processing. Andrew Maas. Stanford University . Lecture 1: Introduction, . ARPAbet. , Articulatory Phonetics. Original slides by Dan . Jurafsky. April 3, Week 1. Course introduction. Course topics overview. Yuchen Fan, Matt Potok, Christopher Shroba. Motivation. Text-to-Speech. Accessibility features for people with little to no vision, or people in situations where they cannot look at a screen or other textual source. Behrooz Chitsaz. Director, IP Strategy. Microsoft Research. behroozc@microsoft.com. Frank Seide. Lead Researcher. Microsoft Research. fseide@microsoft.com. Kit Thambiratnam. Researcher. Microsoft Research. Brad Pitney. Yin Shi. Development Overview. Robot . control . software. Speech recognition. Gesture . recognition. Person . tracking. Music generation. Task Allocation. Brad. Developed robot control software.. Linda Shapiro. CSE 455. 1. Face recognition: once you’ve detected and cropped a face, try to recognize it. Detection. Recognition. “Sally”. 2. Face recognition: overview. Typical scenario: few examples per face, identify or verify test example. “NUGU ” SK Telecom AI Assistant 2017. 2. 27 Dr. Alex JinSung Choi Mic. LED Light 15W Woofer + Tweeter (Tuned by a Professional Audio Company) Bluetooth Launched in Sep.`16 (1 st by an MNO, H ISSN 2277-3878 Volume-1Issue-6 January 2013114Published ByBlue Eyes Intelligence Engineering Sciences Publication Retrieval Number F0446021613/2013BEIESPRecognition of the Tonal Words of BODOLanguage Overview. How . is. . it. . possible. to . recognize. a music clip?. Shazam. Speech vs. music. Speech . recognition. : the . basics. Speech . recognition. : products. Music. A . recognition. . module. Srikar Nadipally. Hareesh . Lingareddy. What is Speech Recognition. A Speech Recognition System converts a speech signal in to textual representation. 3. of 23. Types of speech recognition. Isolated words.