PPT-Structured sparse acoustic modeling for speech separation

Afsaneh Asaei Joint work with Mohammad Golbabaee Herve Bourlard Volkan Cevher φ 21 φ 52 s 1 s 2 s 3 s 4 s 5 x 1 x 2 φ 11 φ 42 2 Speech Separation Problem. Lecture 13. Spoken Language Processing. Prof. Andrew Rosenberg. Linguistics View of Speech Recognition. Speech is a sequence of articulatory gestures. Many parallel levels of description. Phonetic, Phonologic. Speech Recognition . and . Spoken Language Processing. Advanced NLP. Guest Lecture August 31. Andrew Rosenberg. Speech and NLP. Communication in Natural Language. Text:. Carefully prepared. Grammatical. onto convex sets. Volkan. Cevher. Laboratory. for Information . . and Inference Systems – . LIONS / EPFL. http://lions.epfl.ch . . joint work with . Stephen Becker. Anastasios. . Kyrillidis. ISMP’12. DeLiang. Wang. Perception & Neurodynamics Lab. Ohio State University. . & Northwestern . Polytechnical. University. Outline of tutorial. Introduction. Training targets. Separation algorithms. sparse acoustic modeling for speech separation. Afsaneh . Asaei. Joint work with: . Mohammad . Golbabaee. ,. Herve. Bourlard, . Volkan. . Cevher. φ. 21. φ. 52. s. 1. s. 2. s. 3. . s. 4. s. 5. x. Emotion. Julia . Hirschberg. LSA 2017. julia@cs.columbia.edu. Announcement in Canvas about experimental procedures. Has everyone selected their article for presentation?. Discussion questions?. Any recordings?. Michael . Elad. The Computer Science Department. The . Technion. – Israel Institute of technology. Haifa 32000, . Israel. David L. Donoho. Statistics Department Stanford USA. 0/20 MKT1003SUPPORTS GLOBAL BUILDING STANDARDSHelps achieveWELL Building StandardSupports the achievement of WELL v7 Features 78and 80 and WELL v2 Feature S04Helps achieve ecommended reverberation ti DeLiang. Wang. Perception & Neurodynamics Lab. Ohio State University. . & Northwestern . Polytechnical. University. http://www.cse.ohio-state.edu/pnl/. Outline of presentation. Introduction. characterization of dysarthria. Eugenia San Segundo. Dept. Spanish Language & General Linguistics, UNED, Madrid, Spain. Jonathan Delgado . Dept. Developmental and Educational Psychology, La Laguna University, Tenerife, Spain . This textbook has been carefully designed to provide a thorough introduction to the study of speech. It assumes no technical background, and students from a wide variety of disciplines contributing to this new and exciting field will find the exposition fully accessible. Each chapter progresses from simple examples to more detailed discussions of recent primary research and concludes with stimulating problem sets. All topics essential for a basic understanding of the field are included: the physiological, biological, and neurological bases of speech the physics of sound the source-filter theory of speech production and the underlying principles of electrical and computer models of speech production. 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. VOCAL-TRACT. A Case Study in Deep Learning. DeLiang. Wang. Perception & . Neurodynamics. Lab. Ohio State . University. & Northwestern . Polytechnical. University. 2. Outline of . primer. What is the cocktail party problem?. This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications 8211 gradually more advance information is provided giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA) Regularized Discriminant Analysis (RDA) Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features and feature fusion techniques.