Digital Audio Signal Processing DASP - KU Leuvendspuser/dasp/material/Slides_2019… · Digital Audio Signal Processing Version 2019-2020 Chapter-1: Introduction 23 / 32 Case Study:

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Speech & Audio Processing / Part-II

Digital Audio Signal Processing DASP

Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven

[email protected] homes.esat.kuleuven.be/~moonen/

Digital Audio Signal Processing Version 2019-2020 Chapter-1: Introduction 2 / 32

Outline

•  Aims/scope

•  Contents

•  Case study: Hearing instruments

•  Lectures/Exercise Sessions/Exam

Website/Questions

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Aims/Scope

Aim is 2-fold.. •  Speech & audio per se S & A industry in Belgium/Europe

Topics: Noise Reduction / Acoustic Echo & Feedback Cancellation / Active Noise Control / Sound Reproduction / ..etc

•  Develop basic signal processing tools/principles which are also used in many other fields

Spatial filter design (for wireless comms) Adaptive filter algorithms, filtered-X LMS (for active vibration control) Kalman filters (for automatic control, navigation, ..) Time-frequency analysis/processing ..etc


Outline

•  Aims/scope

•  Contents



Website/Questions

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Contents: Chapter-2

Noise Reduction-I Single-Channel Noise Reduction

•  Spectral subtraction methods (spectral filtering) •  Iterative methods based on speech modeling (Wiener & Kalman Filters) Applications: smartphones, conferencing, hearing aids, …

desired signal estimate

desired signal s[k]

noise signal(s)

? ][ks⌢y[k] ][][][ knksky +=

desired signal contribution

noise contribution


Contents: Chapter-3

Noise Reduction-II

Microphone Array Processing - Fixed Beamforming

Referred to as ‘spatial filtering’ (similar to ‘spectral filtering’)

Applications: smartphones, conferencing, hearing aids, …

),(1 θωY

),(2 θωY

),(1 θωY

)(1 ωF

)(2 ωF

)(ωmF),( θωmY

)(ωMF),( θωMY

md),(1 θωY

)(ωS

θ

Σ),( θωZ

θcosmd

Filter-and-sum beamformer

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Contents: Chapter-4 Noise Reduction-III

Adaptive Beamforming & Multi-Channel Noise Reduction •  Adaptive Beamforming

–  Known (fixed) speaker position –  Unknown (time-varying) noise field

•  Multi-channel noise reduction –  Wiener filtering approach = spectral+spatial filtering

Applications: smartphones, conferencing, hearing aids, …


Acoustic Echo & Feedback Cancellation Adaptive filtering problem: •  Non-stationary/wideband/… speech signals •  Non-stationary/long/… acoustic channels

Adaptive filtering algorithms AEC Control AEC Post-processing Stereo AEC

Contents: Chapter-5

5


Contents: Chapter-5 Acoustic Echo & Feedback Cancellation •  Hearing aids, public address (PA) systems •  Correlation between filter input (`x ’) and near-end signal (‘ n ’) •  Fixes : noise injection, pitch shifting, notch filtering, …

Model

F -


Contents: Chapter-6

Active Noise Control •  Solution based on `filtered-X LMS’ •  Application : active headsets/ear defenders

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Contents: Chapter-7

Distributed Signal Processing in Wireless Acoustic Sensor Networks


Guest Lecture: Dr. Enzo De Sena, University of Surrey, UK

‘Sound Field Recording and Reproduction’

Contents: Chapter-8

7


Outline

•  Aims/scope

•  Contents



Website/Questions


Hearing •  Tonotopy of inner ear

Hearing loss •  Aging •  Exposure to loud sounds

= Cochlea

Low-freq tone

High-freq tone

Neural activity for low-freq tone

Neural activitity for high-freq tone

© w

ww

.cm

.be

Case Study: Hearing Instruments 1/10

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DASP Challenges in hearing instruments (next slides) •  Dynamic range compression •  Noise reduction •  Dereverberation •  Acoustic feedback cancellation •  Active noise control •  Etc.

Technology Challenges in hearing instruments •  Small form factor (cfr. user acceptance) •  Low power: 1…5mW (cfr. battery lifetime ≈ 1 week) •  Low processing delay: 10msec (cfr. synchronization with lip

reading)



DASP Challenges: Dynamic range compression Dynamic range & audibility… Normal hearing Hearing impaired `signal dependent amplification’ subjects subjects


Level

100dB

0dB Input Level (dB)

Out

put L

evel

(dB

)

0dB 100dB

0dB

100dB

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•  However: Audibility does not imply intelligibility

•  Hearing impaired subjects need 5..10dB larger signal-to-noise ratio (SNR) for speech understanding in noisy environments

•  Need for noise reduction (=speech enhancement) algorithms: •  State-of-the-art: monaural 2-microphone adaptive noise reduction •  Near future: binaural noise reduction (2 times 2 microphones) •  Not-so-near future: multi-node noise reduction (see below)


SNR

20dB

0dB 30 50 70 90

Hearing loss (dB, 3-freq-average)


DASP Challenges: Noise reduction & beamforming Multimicrophone ‘beamforming’, typically with 2 microphones

e.g. ‘directional’ front microphone and ‘omnidirectional’ back microphone


“filter-and-sum” the

microphone signals

Chapter 3-4

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Future: Multi-node noise reduction in sensor networks/Internet-of-Things


Chapter 7


DASP Challenges: Dereverberation •  Reverb = filtering effect (‘echo-ing’) of acoustic channel in

between speaker and microphone(s)

•  Reverb has an impact on speech understanding

•  Dereverberation = undo filtering by acoustic channel (e.g. ‘inverse filtering’)


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DASP Challenges: Acoustic feedback cancellation •  Problem statement: Loudspeaker signal is fed back into microphone,

then amplified and played back again •  Closed loop system may become unstable (howling) •  Similar to feedback problem in public address systems (for the

musicians amongst you)


Model

F

-

Similar to echo cancellation in GSM handsets, Skype,… but more difficult due to signal correlation

Chapter 5


Chapter 6

DASP Challenges: Active noise control (ANC) ANC to counteract noise leakage & occlusion effect, exploiting additional ‘internal’ reference microphone

Case Study: Hearing Instruments 9/10 ©

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oclo

/Uni

v.O

lden

burg

12



DASP Challenges: …piecing things together


Outline

•  Aims/scope

•  Contents



Website/Questions

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Lectures

Lectures: 1 Intro (count as half) + 7 Lectures PS: Time budget = 7.5*(2hrs)*4 = 60 hrs

Course Material: Slides –  Use version 2019-2020 ! –  Download from DASP webpage

homes.esat.kuleuven.be/~dspuser/dasp/ –  Master copy available @ ESAT B00.10 (Ida Tassens)

Course Prerequisite: DSP-CIS H05F3A/H05F1A (filter design, filter banks, optimal & adaptive filters)


Literature

Literature (general) (available in DSP-CIS library) •  Simon Haykin Àdaptive Filter Theory’ (Prentice Hall 1996) •  P.P. Vaidyanathan `Multirate Systems and Filter Banks’ (Prentice Hall 1993) Literature (specialized) (available in DSP-CIS library) •  S.L. Gay & J. Benesty Àcoustic Signal Processing for Telecommunication’ (Kluwer 2000) •  M. Kahrs & K. Brandenburg (Eds) Àpplications of Digital Signal Processing to Audio and Acoustics’ (Kluwer1998) •  B. Gold & N. Morgan `Speech and Audio Signal Processing’ (Wiley 2000)

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Exercise Sessions/Project Acoustic source localization

–  Direction-of-arrival estimation (‘MUSIC’ Algorithm) –  Noise reduction (‘DoA informed beamforming’) –  Binaural synthesis and 3D audio –  …all in a simulated set-up

Direction-of-arrival θ


..be there !

PS: groups of 2

Exercise Sessions/Project

•  Runs over 4 weeks (non-consecutive) •  Each week

–  1 PC/Matlab session (supervised, 2.5hrs) –  2 ‘Homework’ sesions (unsupervised, 2*2.5hrs)

PS: Time budget = 4*(2.5hrs+5hrs) = 30 hrs •  ‘Deliverables’ after week 2 & 4 •  Grading: based on deliverables, evaluated during sessions

•  TAs: guiliano.bernardi@esat (English+Italian)

randall.ali@esat (English+Spanish)

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•  Oral exam, with preparation time •  Open book •  Grading

7 for question-1 7 for question-2 +6 for project ___ = 20

Exam


•  Oral exam, with preparation time •  Open book •  Grading

7 for question-1 7 for question-2 +6 for question-3 (related to project work) ___ = 20

Retake Exam

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Website

1)  TOLEDO 2)  http://homes.esat.kuleuven.be/~dspuser/dasp/ •  Contact: guiliano.bernardi@esat •  Slides (use version 2018 !!) •  Schedule •  DSP-library •  FAQs (send questions to marc.moonen@esat)


Questions?

1)  Ask teaching assistant (during exercises sessions)

2)  E-mail questions to teaching assistant or marc.moonen@esat 3) Make appointment marc.moonen@esat ESAT Room B.00.14

Documents

Digital Audio Signal Processing DASP - KU Leuvendspuser/dasp/material/Slides_2019… · Digital Audio Signal Processing Version 2019-2020 Chapter-1: Introduction 23 / 32 Case Study: