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Interactive Voice Con

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Interactive Voice Con

  1. 1. Interactive Voice Con Successful smart speakers & voice-enabled products Platinum Sponsor
  2. 2. Introducing the Speakers Paul Beckmann • PhD, MS, and BS from MIT. All in EE. • Technical specialties: signal processing, audio product development, and tools. Mike Klasco • Combined MS/PhD ABT NYU • Audio product development, acoustics, transducers, materials and sourcing 2020 Interactive Voice Con Founder and CTO of DSP Concepts Founder and CEO, Menlo Scientific
  3. 3. Outline • Kickoff • Voice Processing Theory [45 minutes] • Algorithms • Measuring performance • Processor requirements • Product design guidelines • Break [15 minutes] • Demos? [15 minutes] • What Happens in Practice [30 minutes] • Microphone integration issues • The enclosure – the space between the mics and speakers • Loudspeakers, acoustic • Q&A [15 minutes] 2020 Interactive Voice Con
  4. 4. Speech Recognition 2020 Interactive Voice Con
  5. 5. Types of Voice Recognition Algorithms • Voice trigger • Identifies a single word or phrase like “Alexa” or “Hey Siri” • Small vocabulary voice recognition • Fixed vocabulary set for embedded applications. 10’s of words. • “Turn on the lights”, “Next track”, etc. • Full voice recognition • Large vocabulary set. 1,000’s of words • “Play Beatles” • Natural language understanding (NLU) • Combines application specific information for more flexible user interface • “Play Music by the Beatles”, “Give me Beatles Music”, “I want to listen to music by the Beatles” • Can be combined with small vocabulary set 2020 Interactive Voice Con
  6. 6. Audio Front End = Microphone Cleaner 2020 Interactive Voice Con Audio Front End Voice Recognition Mic Array N Channels 1 Channel The Audio Front End (AFE) cleans up signals to improve the performance of the voice recognition. It is like glasses for a camera. Interfering Noise Device Playback Desired Speech
  7. 7. Audio Front End Details 2020 Interactive Voice Con Echo Canceler Trigger Word & Voice Recognition Mic Array N Channels 1 Channel Direction of Arrival Noise Reduction Beam- former Eliminates loudspeaker sound during device playback Determines location of sound source. Used to steer beamformer. Combines multiple microphone signals to improve signal quality. Removes various types of noise
  8. 8. Comparing Amazon and Google • 2 microphones only • 65 to 71 mm spacing • Mono or stereo • High-end application processor required • No variation in products • No variation in performance • Performance lags behind AVS 2020 Interactive Voice Con Google AFE and Trigger Word 3rd Party AFE Amazon Trigger Word ASR ASR • Any number of microphones • Any spacing • Any number of playback channels • Application processor or MCU solutions • Wide variety of designs • 2 to 7 microphones • Different form factors • Better performance • Low cost designs possible
  9. 9. AVS Integration for AWS IoT • Cost effective way to add Alexa voice features • Connects to the cloud • Uses an RTOS and lightweight MQTT network stack • Suitable for low cost microcontrollers • Will expand voice to a much larger number of products 2020 Interactive Voice Con https://docs.aws.amazon.com/iot/latest/developerguide/avs-integration-aws-iot.html (AKA. “Alexa for Microcontrollers”)
  10. 10. Trigger Word • Voice recognition algorithm trained for a single word or phrase • “Alexa”, “OK Google”, “Bixby”, “Siri”, “Cortana”, etc. • Available from multiple suppliers • Amazon, Google, Baidu, etc. • Sensory “Truly Handsfree” • PicoVoice / SoundHound / Cyberon / etc. • They all use machine learning • Often optimized for low power consumption • Sound → Voice Activity Detector → Key word detector • Large models perform better • Sensory: 17 kbyte → 1 Mbyte 2020 Interactive Voice Con
  11. 11. Characterizing Trigger Performance • Probability of False Alarm • How many times does the algorithm accidentally trigger over a 24-hour period? • Probability of Miss • What % of trigger words are not detected by the algorithm • Trigger word algorithms have an adjustable “sensitivity” setting that allows you to tradeoff false alarms and misses. • Amazon requires <3 false alarms per 24 hours of continuous speech 2020 Interactive Voice Con False Alarm Rate ProbabilityofDetection 100% Ideal operating point Tune sensitivity based on allowable false alarm rate
  12. 12. Wake Word Performance in Noise SNR at microphone is main driver of wake word performance • Independent of distance • Independent of room reflections / reverb (for normal household environments) Improve your SNR to improve your wake word performance. 2020 Interactive Voice Con
  13. 13. Beamforming 2020 Interactive Voice Con
  14. 14. Beamforming Principles • Beamformers are spatial filters. They pass signals from certain directions and reduce signals from other directions. • Performance depends heavily upon the geometry of the microphone array • Fixed beamformers utilize FIR filters • Time domain or frequency domain • There are many ways to compute the filter coefficients (MVDR, DAS, etc.) 2020 Interactive Voice Con h1[n] h2[n] h3[n] h4[n] FIR Filters
  15. 15. DSPC Design Method: Maximize SNR • Inputs to design • Microphone geometry • Look angle and beam width • Diffuse field noise level • Microphone SNR • Signal is person’s voice in specified beam • Noise = diffuse field noise + microphone self noise • Iterative design procedure maximizes SNR 2020 Interactive Voice Con
  16. 16. SNR vs. Frequency 2020 Interactive Voice Con
  17. 17. Optimal Array Geometries 2020 Interactive Voice Con Far Field Products 180 or 360 Degree Smart speakers Middle of the room 180 Degree Set-top box Side of the room Flat Line Array TVs, appliances On a wall High-End Standard Low-Cost 40 to 70 mm diameter works. 70 mm works the best 25 mm spacing between mics 75 mm total length +7 dB +6.5 dB +5 dB +2 dB +3 dB +2 dB +4 dB
  18. 18. SNR vs. Mic Geometry Assumptions: • 71 mm diameter • Microphone array is in diffuse field noise with SNR = 50 dB • Speech is at 60 dB in the direction of the beam • Beam width is 45 degrees • Microphone SNR = 65 dB • Look angle = 0 degrees 2020 Interactive Voice Con
  19. 19. Linear Arrays • Linear arrays work well when in an end-fire configuration. • Requires person to be in a specified location. • Provides 4 to 5 dB SNR improvement • Broadside arrays work poorly and should be avoided. • Very little SNR improvement to low frequencies where the bulk of speech energy is • Use broadside arrays only as a last resort when the industrial design dictates no other options • Television • Wall panel 2020 Interactive Voice Con End-fire Broadside Intuition: beamformers use time differences to steer beam. In broadside, voice arrives at the same time at both mics.
  20. 20. Noise Reduction 2020 Interactive Voice Con
  21. 21. Stationary Noise Reduction 2020 Interactive Voice Con Before After Example demonstrates improvement in automotive environments • Effective against: • Fan noise • Automotive road noise • Microphone self noise • Creates a model of the background noise and then removes in real-time • Improves ASR performance by 2 to 3 dB
  22. 22. Interference Canceler • Effective against noise from: • TVs • Appliance self noise • Air conditioners • Requires a minimum of 2 microphones • Combines beamforming, adaptive filtering, and other statistical signal processing techniques • Effective for music and speech interferers • Improves ASR performance up to 30 dB! 2020 Interactive Voice Con 2 Microphone Example
  23. 23. Adaptive Interference Canceler Performance 2020 Interactive Voice Con • Measured in a typical living room environment • Interfering music noise played • Speech at constant level (62 dBC) at DUT • Varied music level • Speech and noise 2 meters from DUT Echo Plus 7-mic DSPC 2- mic DSPC 4- mic 8 dB better DSPC 6- mic 11 dB better Echo 2 7-mic Relative to Amazon Echo Plus and Echo 2
  24. 24. AEC 2020 Interactive Voice Con
  25. 25. Acoustic Echo Cancellers (AEC) • Eliminates loudspeaker sound at the microphone • Enables Voice UI to function while music or text-to- speech is active • Music is usually ducked after the wake word is detected • Best algorithms operate in the frequency domain • Better cancellation • Faster convergence • Lower computation • ERL = Echo Return Loss quantifies performance = How many dB of loudspeaker signal is canceled by the AEC Demo Setup Single microphone with loudspeaker close to the mic. Mono playback in home environment.
  26. 26. Factors Affecting AEC Performance • What type of algorithm are you using? • Time domain vs frequency domain • LMS vs Kalman vs Other? • Echo tail length • How many msec of audio can you cancel? • Longer is better but requires more processing and memory • Far-field smart speakers require 150 to 200 msec of echo tail • Reverberation time of the room (lower is better) • Linearity of your loudspeakers 2020 Interactive Voice Con
  27. 27. Speaker Distortion Affects AEC • This is usually the limiting factor for AEC performance • Loudspeakers distort when playing loud or low frequencies • Speakers need to be tuned to minimize distortion • Rule of thumb: 1% THD AEC up to 40 dB 2% THD AEC up to 34 dB 3% THD AEC up to 30 dB 5% THD AEC up to 26 dB 10% THD AEC up to 20 dB • Product developers must tradeoff low frequency sound quality vs. voice performance 2020 Interactive Voice Con
  28. 28. Rule of Thumb for Speaker Distortion 1. Play a low frequency sine wave through your loudspeaker and plot the spectrum 2. You’ll see harmonics at multiples of the fundamental frequency 3. The largest harmonic determines the absolute limit of the echo canceler 4. ERLE performance based on difference between fundamental and harmonic 5. Repeat at different output levels and frequencies 2020 Interactive Voice Con OK. 30 dB down = 30 dB max ERLE. Bad. 15 dB down = 15 dB max ERLE
  29. 29. AECs and Speaker Processing 2020 Interactive Voice Con Reference signal must be taken after nonlinear processing DRC = Dynamic range compression. This includes nonlinear processing like compressors and limiters EQ Ref DRC DAC AMP EQ Ref DRC DAC AMP Cross- Over Crossovers after the DRC are allowed. Higher order crossover perform better.
  30. 30. Multichannel Echo Cancelers • Some applications require multichannel echo cancelers (e.g., soundbars) • For optimal performance, you need to cancel all the channels. Downmixing reduces performance. • The example to the right shows what happens when you have a 3 channel product and apply a 2 channel AEC 2020 Interactive Voice Con Full performance when using a 3 channel AEC to cancel L, R, and C speakers. Reduced performance when downmixing to 2 channels and using a stereo echo canceler. L’ = L + 0.5 * C R’ = R + 0.5 * C Performance reduced by 5 to 10 dB
  31. 31. Woofer Reference Mic 2020 Interactive Voice Con • Work done in conjunction with Vesper • Uses a new high AOP microphone placed directly in front of the woofer • Advanced processing improves ERL by up to 15 dB • Trigger word performance at max playback level: • Standard processing: 63% • Advanced processing: 91% • Similar feature used in the HomePod
  32. 32. Performance Testing Amazon
  33. 33. Amazon Test Setups 2020 Interactive Voice Con Used for most tests Used for AEC test only
  34. 34. Understanding Amazon Results • False Alarm Tests • Number of false alarms using Amazon’s 24-hour continuous talking test track • The lower the better • Trigger Detection • % of time that the device wakes up when “Alexa” is spoken • Tested in silence, kitchen noise, music noise, and during music playback • The higher the better • Response Accuracy Rate (RAR) • % of time that the cloud accurately understood the question (i.e., “Alexa, what is the capital of China”) • Tested in silence, kitchen noise, and music noise • The higher the better 2020 Interactive Voice Con
  35. 35. Testing Scenarios Silence No interfering sound, uttering “Alexa” at 62 dBC Kitchen Noise (0, -3 dB, -6 dB) Alexa utterance at 62 dBC / Noise at 62, 65, and 68 dBC Music Noise (0, -3 dB, -6 dB) Alexa utterance at 62 dBC / Music at 62, 65, and 68 dBC Acoustic Echo Canceler Music playback at 90 dBC while trigger words are played at 62 dBC. 2020 Interactive Voice Con
  36. 36. Living Room Results – Trigger Detection 2020 Interactive Voice Con
  37. 37. Living Room Results - RAR 2020 Interactive Voice Con
  38. 38. Processor Requirements
  39. 39. Many Performance Levels Low Power / Near-field 1 or 2 mics ARM Cortex-M4 20 to 30 MHz Basic Far-Field 2-mics. Mono ARM Cortex-M7 or Cortex-A53 200 MHz High-Performance Far-Field 4+ mics. Stereo ARM Cortex-A53 350 to 600 MHz High-Performance Far-Field 4+ mics. Multichannel ARM Cortex-A53 900 to 1200 MHz 2020 Interactive Voice Con
  40. 40. Processor Comparisons 2020 Interactive Voice Con ARM Cortex-M4 ARM Cortex-M7 ARM Cortex-A35 ARM Cortex-A53 ARM Cortex-A72 Tensilica HiFi 4 0.26 0.45 0.37 0.48 0.98 1.00 Processor efficiency per MHz. The larger the better. ST, NXP, Renesas, Ambiq, Quicklogic ST, NXP Mediatek NXP, Amlogic, Qualcomm Coming soon! NXP, Mediatek, Amlogic ARM Cortex-A53 is the sweet spot for smart speakers.
  41. 41. Recommended Designs
  42. 42. Smart Speaker Designs • 360-degree operation • Microphones on top of product • 40 to 75 mm diameter • Physically separate microphones and loudspeakers for best performance • Mono or stereo playback High-End Standard 2020 Interactive Voice Con
  43. 43. Sound Bar Designs • 180-degree operation • Microphones on top of product near center of device • 60 to 75 mm design • Physically separate microphones and loudspeakers for best performance • Stereo or multichannel playback (up to 7 reference channels) • Compatible with Dolby Atmos High- End Standard 2020 Interactive Voice Con
  44. 44. TV Designs Placement options • Top is better than bottom • Further away from speakers • Bottom usually wins out because of lower cost • Mics do not have to be centered • 2 mics sufficient 2020 Interactive Voice Con Good Better
  45. 45. Set-Top Box Designs • Top of Device • 180-degree operation • Microphones on top of product • Tethered “puck” • 360-degree operation • Microphones on top of product • Support for optional internal speaker for voice playback • Audio playback through HDMI High- End Standard 2020 Interactive Voice Con
  46. 46. Appliance / Tablet Designs • 180-degree operation • 2 or 4 microphone linear array • 25 to 75 mm design • Physically separate microphones and loudspeakers for best performance • Mono or stereo playback Good Better 2020 Interactive Voice Con
  47. 47. Design Guidelines – Microphones 2020 Interactive Voice Con Far Field Products • Microphones should be placed on the top of the product, if possible. • Microphones should be on a flat horizontal surface • Microphones should be visible to the user (not occluded) • Flat line arrays are not recommended. These are only last choice, if necessary. (Microphone arrays work best if the microphones are displaced in the horizontal plane) • Microphones need to be properly ported (see design guidelines from microphone vendor) • 4 microphones is sufficient for most products
  48. 48. Design Guidelines – Microphones 2020 Interactive Voice Con Far Field Products • SNR of 65 dB. Higher SNRs provide no benefit for voice recognition but has benefits for voice communication • Gain matching: • +/- 1 dB in the range 200 to 6 kHz (recommended) • +/- 1dB in 200 to 4 kHz and +/-3 dB in 4k to 7 kHz (required) • Microphone AOP must be high enough so that the system doesn’t clip when loudspeakers are played at full volume. Recommendations: • 120 dB for smart speakers • 130 dB for sound bars • 40 to 70 mm microphone spacing is recommended. As small as 20 mm is possible with some degradation in performance.
  49. 49. Microphone Acoustical Porting 2020 Interactive Voice Con (No Common Cavity) MEMS Mic Vent hole Case PCB MEMS Mic Vent hole You need individual gaskets to make a direct connection between each mic and its vent hole If you block a microphone hole with putty, you should see the level drop by at least 30 dB MEMS Mic Case PCB MEMS Mic Gasket Gasket This design with a common cavity shared by all microphones won’t work.
  50. 50. Design Guidelines – Microphones (A) 2020 Interactive Voice Con In Ear Products • 2 microphones are sufficient for most products • Use 2 microphones in an end fire configuration pointing towards the mouth • Space microphones as far apart as possible. 10 mm is the minimum spacing. 20 mm is preferred • Microphone on end of “boom” improves performance
  51. 51. End of first session
  52. 52. Overview 2020 Interactive Voice Con What Happens in Practice • Microphone selection • The Physical world in front of the mic • No Man’s Land between the mic and speaker (leakage) • Loudspeakers – good, bad and ugly • Software integration issues
  53. 53. MEMs Microphone selection cheat sheet • Analog or digital? • Analog single-ended or balanced? • Top or bottom port? • Standard size or compact ? • AOP – Acoustic Overload Point? • S/N – Signal to Noise? • Sensitivity (asic gain)? • Robustness (IPXX)? 2020 Interactive Voice Con
  54. 54. MEMs Microphones – what is inside? • MEMs mic element + ASIC in a package • Wiring between mems mic die and ASIC • Typical package envelope of 3.50mm x 2.65mm x 0.98mm • Smaller foot print on some models but reduced back volume = reduced s/n • Faraday shield on some models 2020 Interactive Voice Con
  55. 55. Microphones - Analog vs digital? What are the mic inputs on codec or soc (System On Chip)? • Analog single-ended • Analog pseudo balanced • Digital – PDM 2020 Interactive Voice Con
  56. 56. Microphones – Top or Bottom port? • The MEMs smt package can have the sound aperture either on the top or bottom • If on the bottom then the circuit board it is flow soldered to the flex pcb) and have a hole that aligns to the MEMs mic port • Bottom port warning • Sealing - back port smt seal eyelet 2020 Interactive Voice Con
  57. 57. Microphones – signal to noise • S/N was once a deal killer for most serious applications, MEMs mics have caught up with ECMs with commodity analog and digital MEMs reaching beyond 60 dB s/n. • Active noise canceling headphones, hearing aides, voice command desire 65 dB s/n or better • 70+ dB from a few vendors by the start of 2021 (but this keeps slipping!) • Better s/n = less mics? Some discussion of higher s/n enables reduction in mics required 2020 Interactive Voice Con
  58. 58. Microphones • Analog MEMs mics - single-ended or balanced differential outputs? • balanced output analog is good defensive engineering if your product will have longer wire runs, digital noise, emi/rf floating around • How differential is MEMs mic topology? True differential capacitive MEMs mics use dual grids for improved noise immunity over single ended for high noise immunity 2020 Interactive Voice Con
  59. 59. Microphones - Digital • Digital MEMs mics offer greater immunity to interference than analog MEMs • time to market considerations avoiding having to tweak and rework your board layout if noise problems await you, then digital is the way to go • If the mic performance is critical for your type and class of product analog may be better with external premium codec (both AOP and noise floor 2020 Interactive Voice Con
  60. 60. Microphones – Acoustic Overload Point (AOP) • Is AOP due to mic element saturation vs asic overload clipping? • MEMs analog mics typically have better acoustic overload point (aop) which is where serious distortion sets in (codec overload before MEMs mic element) • Analog MEMs overload a bit more gracefully than digital as when an A/D codec overloads it is a line in the sand and nasty. • Digital MEMs aop can be as low as 116 dB and more typically 120 dB. Analog aop tends to be over 120 dB and can be 130+ dB on some MEMs mics. • Vesper’s piezo MEMs mics have versions with very high AOP. 2020 Interactive Voice Con
  61. 61. Microphones - Directivity • MEMs mics are omni-directional • For achieving directional characteristics they are used in arrays • One requirement for mic arrays is that the mics are closely matched in sensitivity and response and will be able maintain that uniformity over time 2020 Interactive Voice Con
  62. 62. The physical world in front of the mic 2020 Interactive Voice Con
  63. 63. Microphones – the world around the mic Key topics • MEMs mics are mounted to flex PCB using smt reflow along with the rest of the smt components • Port Helmholtz resonance – moving it out of band • The port and wind noise • Laminar entry • Acoustic mesh 2020 Interactive Voice Con
  64. 64. Microphones - What are membranes for? Woven and non-woven used for; • wind noise, water blocking • acoustic resistance determines crossover to DSP wind noise filtering • Dust problems – internal membrane (within package) blocks smt reflow gasses • Field use issue - shift over time - gunk in the membrane over the mics facing facing stove top 2020 Interactive Voice Con
  65. 65. Microphones – the world around the mic Wind noise blocking/acoustic mesh • Mic element overloaded/ saturated by wind • Wind pressure must be blocked acoustically (acoustic resistance membrane) • Mic overload cannot be fixed by DSP (but some turbulence can be filtered out) • Acoustic mesh can also block liquids • (hydrophobic & oleophobic ) 2020 Interactive Voice Con
  66. 66. Microphones – the world around the mic Port and wind noise • Laminar entry (flared aperture) • (turbulence in port to be avoided) • Port Helmholtz resonance peak – moving it out of band • Acoustic mesh damps peak Q 2020 Interactive Voice Con
  67. 67. The physical world between the mic and speaker 2020 Interactive Voice Con
  68. 68. Leakage between the mic & speaker Audio output leakage is both airborne and through the enclosure structure • Minimizing Airborne leakage • keep the mic(s) and speakers as far apart as possible • avoid overlapping the mic(s) pickup pattern and speaker radiation pattern • Structural transconduction (microphonics) • Enclosure housing – ribs, joints, wall thickness • Plastics are not all equal • speaker sub-enclosure isolation mounts (grommets or gaskets) • mic isolation 2020 Interactive Voice Con
  69. 69. - Construction and Materials • Plastics have different acoustical characteristics • Stiffness and damping are key factors • Compatibility considerations • Shrink • Tool temperature • Flow • Impact strength • Sink marks/wall thickness 2020 Interactive Voice Con
  70. 70. - Construction and Materials The Incumbent plastics • ABS • PC • ABS+PC • PP 2020 Interactive Voice Con
  71. 71. - Construction and Materials • TreBlend (Ineos) PA/SAN • Cellulose Plastics • Treva (Eastman) • Symbio (Sappi) • Thicker walls/ ribs without sink marks Acoustically engineered plastics 2020 Interactive Voice Con Genelec M040 – NCE enclosure
  72. 72. The physical world of speakers and the AEC Achilles heel - distortion 2020 Interactive Voice Con
  73. 73. - Enclosure Mechanical Engineering E • Open the window more and more bugs come in • More power and more bass = no gain without pain • Increase acoustic output before feedback and AEC breakdown by reducing the cabinet resonance peak • Extending low-end response of product will shake things up more 2020 Interactive Voice Con
  74. 74. Speaker Nonlinearities AEC issues • Speaker distortion nonlinearities are the enemy of AEC • Loudspeaker nonlinearities effect AEC • - low-end distortion impact on aec yet not audible for listening • Fine tuning of suspension and motor nonlinearities are critical • or source off-the-shelf application-specific speakers optimized for AEC and ANC 2020 Interactive Voice Con
  75. 75. - 50 mm AEC / ANC optimized speakers • Application-specific ANC and AEC high linearity /lower distortion speakers to meet TIA 930 • Typically around 50 mm diameter • SEAS • Tymphany • Stetron 2020 Interactive Voice Con
  76. 76. subVo servo feedback correction Next generation solution for increased AEC headroom • subVo bend-sensor provides distortion reduction at the lower octaves enabling increased AEC headroom • Precision position sensor provides error correction feedback • 10 dB of feedback = 10 dB of piston range distortion reduction 2020 Interactive Voice Con
  77. 77. Software Integration Issues 2020 Interactive Voice Con
  78. 78. Software Integration Challenges • Real-time CPU load • Wrong interrupt levels • Dropping samples / blocks • Non constant latency between mics and reference signals • Misconfigured PDM filters • Different clocks for mics and reference signals 2020 Interactive Voice Con
  79. 79. Example #1: Noisy PDM Microphones PDM to PCM Converter PCM Samples PDM Bitstream Problem Statement • ASR accuracy only 72% in quiet speech conditions • High quality microphone: • -41 dB sensitivity / 66 dB SNR • Noise floor expected at 28 dBA • Noise floor measured at 39 dBA • Root cause • PDM to PCM converter was implemented with 16-bit math • Generated noise floor was at -96 dBFS → 39 dBA • Solution • Implement PDM to PCM conversion in software • ASR accuracy improved to 94%
  80. 80. Example #2: Incorrect thread priorities CPU Load Problems Audio processing was taking 18% on average but there were large spikes. Bluetooth thread priority was incorrectly set higher than real-time audio processing. Corrected Thread Priorities Steady and consistent CPU load 0 20 40 60 80 100 120 140 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 CPU Load over Time Peak Average 0 10 20 30 40 50 60 70 80 90 100 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 CPU Load over Time Peak Average
  81. 81. Q&A 2020 Interactive Voice Con
  • StevieRhim

    Jul. 18, 2020
  • GaryBonie

    Jul. 9, 2020
  • sujatharatnala1

    Jul. 9, 2020
  • RosalfonsoBortoniDSc

    Jul. 9, 2020

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