week4 goldwave by 8P6Cqm4

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									AUDIO SIGNAL PROCESSING
            Health Informatics
                 Week 4
      Supplementary Material for Lab
INTRODUCTION
   The purpose of this lab class is to:
       Outline, using practical examples, the challenges in
        recording acoustic sounds within real-word ‘noisy’
        environments.
       Use software tools to process and remove noise from
        acoustic signals.
       Case Study: Stethoscope

   The lab class with be split into 2 parts:
       Some self directed reading of theory material contained
        within these slides.

       Practical session using audio signal processing
        techniques.
OVERVIEW
   In this tutorial we will introduce and apply some basic concepts in signal
    processing.
   The tutorial will focus on ‘audio signal processing’.
   Throughout the tutorial we will be using a piece of specialised signal
    processing software.
      GoldWave is a professional digital audio editor that plays, records,
       edits, processes, and converts audio on your computer.
   The purpose of this tutorial are to introduce some basic concepts and
    apply these concepts to four tasks:
     Examine how filtering techniques effect
      speech.
     Resample CD quality recordings.
     Remove unwanted background noise from
      a speech recording.
     Remove unwanted speech from a Stethoscope
      recordings
INTRODUCTION
   Signal processing is the investigation, interpretation and modification
    of signals such as audio and image.
   Typically applied to classify a pattern based on its characteristics,
    identify particular patterns from a given signal, or to remove
    redundant information (noise) from a signal.
       Clean up a radio broadcast.
       Extract a public speaker’s speech from an audio sample which contains
        audience applause.
   The extraction of useful information from a particular signal has
    several applications within the healthcare domain, for example:
       Identifying patterns in an Electrocardiogram.
       Extracting heartbeat or lung sounds in the presence of mechanical
        instruments during surgery i.e. saw, drill.
       Identify a sequence of daily living activities through the separation of
        various sounds, for example, brushing teeth versus washing.
   Typical processing techniques include:
       Filtering, compression, spectral analysis, digitisation and reconstruction.
AUDIO SIGNAL PROCESSING
   Audio signal processing is the term used to describe the
    modification of auditory signals or sounds.

   As audio signals may be electronically represented in either
    digital or analog format.
       Analog processors operate directly on the electrical signal, while digital
        processors operate mathematically on the binary representation of that
        signal.

   An analog representation is usually electrical; a voltage level
    represents the air pressure-waveform of the sound.

   A digital representation expresses the pressure wave-form as a
    sequence of binary numbers.
      This permits signal processing using digital circuits such as
       microprocessors and computers.
      This conversion is prone to some loss of quality.
AUDIO SIGNAL PROCESSING CONT.
   In order to convert the continuous-time analog signals to a
    discrete-time digital signals, it must be sampled and quantized.
      Sampling is the division of the signal into discrete intervals at
       which analog voltage readings will be taken.
      Quantization is the conversion of analog voltages into a
       binary representation; this is performed by an analog-to-
       digital converter.

   The length of the sampling interval determines the maximum
    frequency that can be encoded. The Nyquisty-Shannon sampling
    theorem states that a signal can be exactly reconstructed from its
    samples if the sampling frequency is greater than twice the
    highest frequency of the signal.

   For example, the human hearing extends from approximately 20
    Hz to 20000Hz (20kHz).
       To reproduce a ‘good’ recording of a person’s speech the sampling rate
        has to be above 40 KHz - commercial CDs are recorded at 44.1 KHz!
SAMPLES
   Digital audio is composed of thousands of numbers (samples).
   Each sample holds the state, or amplitude (loudness) of a sound
    at a given instant in time. For digital audio, all the samples
    combine to make a waveform of the sound.




   When playing audio, each sample specifies the position of the
    output speaker at a certain time.
       Small numbers moves the speaker in
       Large numbers moves the speaker out.
   This movement occurs thousands of times per second, causing
    vibration, which we hear as sound.
SAMPLE RATE
   The sampling rate is the number of times, per second, that the amplitude
    level (or state) is captured. It is measured in Hertz (Hz).
       high sampling rate results in high quality digital sound in the same way that high
        resolution video shows better picture quality.
       CDs, for example, use a sampling rate of 44100Hz, whereas telephone systems use
        a rate of only 8000Hz.
       Higher sampling rates capture a wider range of frequencies and maintain a
        smoother waveform.
       The figure below shows a real world waveform in red and the digital waveform in
        black at different sampling rates.
       You can see that increasing the sampling rate makes each step of the digital
        waveform narrower. The shape more closely follows the real world.
       In simple terms, the sampling rate controls the
        width of each step.
   The rate to use depends upon the type of
    sound and the amount of storage space
    available.
   Higher rates consume a lot of space.
       the CD requires over 5 times the amount
        of storage as the telephone system for the
        same digital sound.
        Certain types of sounds can be recorded at lower rates without loss of quality.
THE SINE WAVE
   To the human ear, a sound is made up of a number of sine waves.

   This wave pattern occurs often in nature, including ocean waves, sound waves,
    and light waves

   You can prove this using Matlab!!

        1




      0.8




      0.6




      0.4




      0.2




        0




      -0.2




      -0.4




      -0.6




      -0.8




       -1
        -10   -8     -6      -4     -2      0      2      4       6      8      10




   Sine waves can be used as simple building blocks to 'make up' and describe nearly
    any periodic waveform including squares waves (digital representation of audio)
    or even the irregular sound waves made by human speech.
    SIMPLE BUILDING BLOCKS
                        1




                     0.8




                     0.6




                     0.4




                     0.2




    sin(x)              0




                     -0.2




                     -0.4




                     -0.6




                     -0.8




                       -1
                        -10    -8   -6   -4   -2   0   2   4   6   8   10




                     0. 4
                                                   +
                     0. 3




                     0. 2




   sin(3x)/3         0. 1




                        0




                     -0. 1




                     -0. 2




                     -0. 3




                     -0. 4
                         -10   -8   -6   -4   -2   0   2   4   6   8   10




                                                   =
                        1




                     0.8




                     0.6




                     0.4




                     0.2




sin(x) + sin(3x)/3      0




                     -0.2




                     -0.4




                     -0.6




                     -0.8




                       -1
                        -10    -8   -6   -4   -2   0   2   4   6   8   10
      SIMPLE BUILDING BLOCKS
                                     1




                                   0.8




                                   0.6




                                   0.4




                                   0.2




      sin(x)                         0




                                  -0.2




                                  -0.4




                                  -0.6




                                  -0.8




                                    -1
                                     -10    -8   -6   -4   -2   0   2   4   6   8   10




                                   0. 4
                                                                +
                                   0. 3




                                   0. 2




                                   0. 1




    sin(3x)/3                        0




                                  -0. 1




                                  -0. 2




                                  -0. 3




                                  -0. 4
                                      -10   -8   -6   -4   -2   0   2   4   6   8   10




                                   0. 2
                                                                +
    Sin(5x)/5
                                 0. 15




                                   0. 1




                                 0. 05




                                     0




                                 -0. 05




                                  -0. 1




                                 -0. 15




                                  -0. 2
                                      -10   -8   -6   -4   -2   0   2   4   6   8   10




                                     1
                                                                =
                                   0.8




                                   0.6




                                   0.4




                                   0.2




                                     0


sin(x) + sin(3x)/3 + sin(5x)/5    -0.2




                                  -0.4




                                  -0.6




                                  -0.8




                                    -1
                                     -10    -8   -6   -4   -2   0   2   4   6   8   10
  TOWARDS A SQUARE WAVE
                  1




                0.8




                0.6




                0.4




                0.2




7 sine waves      0




                -0.2




                -0.4




                -0.6




                -0.8




                 -1
                  -10   -8   -6   -4   -2   0   2   4   6   8   10




                  1




                0.8




                0.6




                0.4




14 sine waves
                0.2




                  0




                -0.2




                -0.4




                -0.6




                -0.8




                 -1
                  -10   -8   -6   -4   -2   0   2   4   6   8   10




                  1




                0.8




                0.6




                0.4




                0.2




50 sine waves     0




                -0.2




                -0.4




                -0.6




                -0.8




                 -1
                  -10   -8   -6   -4   -2   0   2   4   6   8   10
HUMAN AUDIO RANGES
      The human ear can hear frequencies from 20 Hz to
       20,000 Hz
      Human voice or speech ranges from 300 Hz to 3,400
       Hz
Amplitude




            20   300   3,400                       20,000

                               Frequency (Hertz)
            FILTERS
               Filters are used to remove a range of frequencies from a sound and can
                produce a variety of effects.
               At a basic level there are 4 types of filters.
                    Lowpass.
                    Highpass.
                    Bandpass
                    Notch
Amplitude




                                                                                  Notch
                Low Pass                 High Pass           Band Pass




                                         Frequency (Hertz)
FILTERS - EXAMPLE
   Lowpass filters block high pitched frequencies but allow low
    pitched frequencies to pass. They can be used to reduce high
    end hiss noise or remove unwanted sounds above the given
    cutoff frequency.
          If you were to apply a lowpass filter with a cutoff frequency of
           1000Hz on speech, it would make it sound mumbled and deep.
   Highpass filters block low pitch frequencies, but allow high
    pitched frequencies to pass. They can remove deep rumbling
    hum or remove unwanted sounds below the given cutoff
    frequency.
          If you were to apply a highpass filter with a cutoff frequency of
           1000Hz on speech, it would make it sound thin and hollow.
   Bandpass filters block all frequencies outside a specified range,
    keeping only frequencies within the range.
   Notch filter remove all frequencies inside specified range,
    keeping only frequencies outside the range. Typical a notch filter
    can be used to remove noise at a particular frequency such a
    50Hz main supply in electrical systems.
PRACTICAL OVERVIEW
   Download GoldWave
   Test Headset including microphone (sharing may be necessary)
   Show a real life example of filtering (Example)
     Before
     After

   Run some example filters (Task 1)
       See effects on speech
           Low pass filter
           High pass filter
   Record CD quality audio @ 44,100Hz (Task 2)
           Resample to 15,000 Hz to simulate radio.
           Resample to 8,000 Hz to simulate telephone line.

   Remove an unwanted high pitched signal from a speech
    recording (Task 3)
   Remove some unwanted speech sounds from a audio recording of a
    patient breathing (Task 4)
DOWNLOAD GOLDWAVE & AUDIO
FILES
 Check if goldwave installed!!
 If not, download Goldwave.
     Goldwave is a software suite that allows some signal
      processing capabilities such filtering audio signals.
     http://www.goldwave.com
     Click on download on left hand side
     Self-Installing GoldWave v5.25

   Download all the audio files required for this
    tutorial.
     Task3.wav (speech containing high pitched noise)
     Task4.wav (breathing sounds with 2 types of noise)
TESTING YOUR MICROPHONE
   If you do not have a microphone then you may
    download a sample speech file from the web.

   Otherwise:

   Step 1: File > New;
     Select DVD Quality Reset.
     Press OK.

 Step 2: Press the record icon and speak into the
  microphone.
 Step 3: Press the play icon to verify the recording.
EXAMPLE OF BACKGROUND NOISE
         FILTERING



   Noise Type       Filter   Before   After


   Pulse Oximetry   Notch


   Vocal            Kalman
TASK 1
   Record a short sample of your own speech – or use
    sample file.
     Save audio file as Task1.wav
     5 – 10 seconds for example count to 10.
     Apply Low Pass Filter @ 1,850 Hz




         300                              3,400
                    Low Pass @ 1,850 Hz




         300          1,850               3,400
TASK 1
   Applying a Low/High Pass filter
     Select the ‘Low/Highpass’ icon from the menu
     The following dialog box should appear



                                                     Frequency cutoff
                                                     selector

Low/Highpass
Selector                                             Used to select the
                                                     steepness of the
                                                     cutoff. The higher
                                                     the number the
                                                     steeper the cutoff.
TASK 1
   Apply High Pass Filter @ 1,850 Hz
                    High Pass @ 1,850 Hz




        300          1,850                 3,400


   Apply Low Pass Filter @ 800 Hz
                    Low Pass @ 800 Hz




        300   800                          3,400
TASK 1
   Apply High Pass Filter @ 2900 Hz
                 High Pass @ 1,850 Hz




        300                    2900     3,400


   Apply Low Pass Filter @ 300 Hz
                 Low Pass @ 800 Hz




        300                             3,400
TASK 2
 Record        a short sample of your own
    speech.
       CD quality sample rate of 44,100 Hz
   Resample the audio stream at 15,000 Hz
       Radio
   Resample the audio stream at 8,000 Hz
       Public Switched Telephone Network
TASK 2
 Resampling        an audio file
    Select the ‘Resample’ icon from the menu
    The following dialog box should appear
TASK 3
   Load the file called Task3.wav into GoldWave
   Remove a high pitched noise from a speech recording
   Apply the appropriate filter type and select the correct cut off frequency to remove the high
    pitched noise.

   Apply Low Pass Filter @ 2,000Hz




                           Low Pass @ 2,000 Hz




          20                 2,000                       20,000
TASK 4 - OVERVIEW
   In this task you will be given the opportunity to
    extract breathing sounds from a recording
    containing background noise in the form of people
    talking.

   The recording was taken using a stethoscope.

   In particular, an electronic stethoscope was used.
       This is an example of an emerging technology which is
        assisting clinicians to improve disease detection.
       What follows is a brief introduction into the use of
        stethoscopes.
CASE STUDY: STETHOSCOPE
   Since 1816, the stethoscope has been an invaluable diagnostic tool in respiratory and cardiovascular
    evaluation.

   Detected abnormalities indicate pathological conditions of the airways or lungs.

        for example, respiratory sounds recorded over chest wall with abnormally high frequencies (600-
         1000Hz) can indicate diseases with airway obstruction - asthma and chronic bronchitis.

   Nonetheless, can be limited. Information obtained is subjective and dependent on expertise of the
    examiner.

        Does not result in permanent objective records that can be documented!

   Further disadvantage is the fact that physical readings can only rely on the auditory capability of the
    user.

   Modern technology can now be used to great advantage for the capture, storage, analysis and
    communication of sounds normally heard through the stethoscope.

   Digitization of respiratory sounds using an electronic stethoscope is easily achievable, resulting in a high-
    quality permanent representation that can be documented, duplicated and analysed using digital signal
    processing techniques.

   Coupled with automated computer-based decision making techniques, signal processing methods can be
    applied in order to advance the practices and procedures used in modern-day respiratory monitoring.
ELECTRONIC STETHOSCOPE
   Modern day electronic stethoscopes to not rely on mechanical
    components such as diaphragms.


   Instead a transducer is used as the sensor and converts the
    sounds (mechanical vibrations) to an electronic signal.


   These signals are then played through a headset or can be
    channelled to recording apparatus for storage and future
    processing.


   The main advantage of this approach over the analogue
    counterpart is that intelligence can be added to the device.


   This allows filtering and enhancement of the signals, something
    not possible to do with the analogue version.
TASK 4

     the file called Task4.wav into
 Load
 GoldWave.

 Usingthe skills you have gained
 attempt to remove the background noise
 (speaker’s voice) from the recording.

								
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