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Sounds of Silence The Challenge for AI B.Yegnanarayana Speech and Vision Lab Dept. of CS&E, IIT Madras Goal of Artificial Intelligence The urge is to make machines more intelligent But in the process we are doing the opposite Why? Because we are only storing and manipulating data What is INTELLIGENCE? It is not simply manipulation of data Intelligence of human beings Capture, associate and retrieve patterns Examples Signatures, face recognition, video < Prev Next > Why AI is difficult: Some examples Representation of 1D, 2D, 3D data Contrast Reading vs writing Listening vs speaking Looking vs sketching Watching vs doing Recognition vs synthesis Key is learning Development of motor control is slow Intelligent activity Involves linking key features/concepts/ideas < Prev Next > Intelligence vs Information Creating an environment for intelligent activity Current methods do exactly the opposite We present more data more frequently No scope for acquiring implicit pattern behavior Confusion between knowledge and information Knowledge society or ignorance society Filling up mind with data is like filling up silence Intelligence is in capturing the sounds of silence < Prev Next > Sounds of Silence Significance of silence In cartoons and string of characters Examples of silence in speech sounds A sufficient cue A necessary cue Illustrations from continuous speech Waveform, residual and impulses Different speakers Different languages Perception of Sounds of Silence Human ability and machine's inability - Why? < Prev Next > Architectural Mismatch Machines take mostly silence and may ignore signal Representation Machine Human Pixels/samples (mostly silence data) Symbols and interrelations (ignores silence) Multiple (neurons) Processor Single Processing Sequential (local) < Prev Parallel and distributed (local and global) Next > Nature of AI Problems Data String of Characters Information Words/ Sound Units Speech Sequence of Samples Formants & Pitch Image Array of Pixels Objects & Interrelation Natural Language Knowledge Intelligence Rules Message (Syntax) Intonation & Duration Message (language constraints) Rules to Message form picture Decision making < Prev Next > Illustrations from Speech • Nature of speech production and perception • Challenges in speech recognition, synthesis, and speaker recognition • Why they are difficult for machine and easy for us? • Due to our ability to capture sounds of silence < Prev Next > Characteristics of Human Problem Solving • Computing sounds of silence • Essentially pattern processing instead of data processing • Integration of local and global patterns • Delayed decisions • Nonuniqueness of solutions < Prev Next > Architectural Features of Possible New Models Need to move from • Deterministic computation to decision logic • Sequential processing to PDP • Set of equations to set of inequalities • Problem solving to learning • Data processing to multidimensional pattern processing < Prev Next > Conclusions • Powerful computers need not solve intelligent problems • Finer sampling need not result in good solutions • Two interesting problems: Video processing and dictation machine • The challenge is computing the sounds of silence • Unless we watch, the technology may destroy itself by exposing its limitations. • Dont forget that it is always the human being is the reference not the machine for intellectual abilities. < Prev Next > Thank you < Prev Next > Back < Prev Next > Some Illustrations of “Sounds of Silence” Silence: A sufficient cue for stop consonant perception slit split s_lit 30 ms 150 ms 600 ms Silence: A necessary cue for stop consonant perception sha shka 10 ms 100 ms Back < Prev Next > Some Illustrations of “Sounds of Silence” Signal Residual Instants More examples : Signal, residual and instants Some more examples : Signal, residual and instants Back < Prev Next > Speech Production Mechanism Back < Prev Next > Still Frame Video Sequence Less noise More noise < Prev Next > Still Frame Video Sequence Less noise More noise < Prev Next > Back < Prev < Prev