Sounds of Silence The Challenge for AI

B.YegnanarayanaSpeech and Vision Lab

Dept. of CS&E, IIT Madras

The urge is to make machines more intelligentBut 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 beingsCapture, associate and retrieve patterns

ExamplesSignatures, face recognition, video

Goal of Artificial Intelligence

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Representation of 1D, 2D, 3D data

ContrastReading vs writingListening vs speakingLooking vs sketchingWatching vs doingRecognition vs synthesis

Key is learning Development of motor control is slow

Intelligent activityInvolves linking key features/concepts/ideas

Why AI is difficult: Some examples

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Intelligence vs Information

Creating an environment for intelligent activityCurrent methods do exactly the opposite

We present more data more frequentlyNo scope for acquiring implicit pattern behavior

Confusion between knowledge and informationKnowledge society or ignorance society

Filling up mind with data is like filling up silence Intelligence is in capturing the sounds of silence

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Sounds of SilenceSignificance of silence

In cartoons and string of characters

Examples of silence in speech soundsA sufficient cueA necessary cue

Illustrations from continuous speechWaveform, residual and impulsesDifferent speakersDifferent languages

Perception of Sounds of SilenceHuman ability and machine's inability - Why?

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Architectural MismatchMachines take mostly silence and may ignore signal

Machine Human

Representation Pixels/samples(mostly silence data)

Symbols andinterrelations

(ignores silence)Processor Single Multiple

(neurons)

Processing Sequential(local)

Parallel anddistributed

(local and global)

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Nature of AI ProblemsData I nformation Knowledge I ntelligence

NaturalLanguage

String ofCharacters

Words/Sound Units

Rules(Syntax)

Message

SpeechSequence of

SamplesFormants &

Pitch

Intonation &Duration

(languageconstraints)

Message

ImageArray ofPixels

Objects &Interrelation

Rules to form picture

Message

Decisionmaking

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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

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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

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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

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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.

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Thank you

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Back

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Some Illustrations of “Sounds of Silence”

30 msslit

150 ms split

600 ms s_lit

10 ms

100 ms

sha

shka

Silence:

A sufficient cue for stop

consonant perception

Silence:

A necessary cue for stop

consonant perception

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Signal

Residual

Instants

Some Illustrations of “Sounds of Silence”

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More examples : Signal, residual and instants

Some more examples : Signal, residual and instants

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Speech Production Mechanism

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Still Frame Video Sequence

Less noise

More noise

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Still Frame Video Sequence

Less noise

Morenoise

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