Multimedia Networking Project 1

Speech Detection

Due date (extended): September 16, 2010, by 11:59pm


Index


Overview

An important feature of multi-person audioconference is detecting speech in the presence of background noise. This problem, often called speech detection, boils down to detecting the beginning and ending of a section of speech, called a talk-spurt. By removing silent periods between talk-spurts, network bandwidth and host processing can be greatly reduced. Moreover, end-host applications often use the times between talk-spurts to reset their delay buffers.

Rabiner and Sambur [RS75] describe an algorithm which locates the endpoints of a talk-spurt based on an algorithm that uses the zero crossing rate and the energy. While the paper is relatively old (published in 1975) zero crossings and energy are still the basis for many speech detection algorithms.

You will implement the Rabiner and Sambur algorithm in an application that records speech from a microphone. Your program will store two versions of the sound, one with all the sound recorded and the other with sound removed. In addition, your program will store a third file of data in text format, allowing you to graph the captured audio signal, energy computations and zero level crossings.


Details

You will write a program, called record, that records sound from the microphone until the user presses ctrl-c and exits. Your program will produce 3 files as output:

(Be careful as you do your recording, as all three files can get large quickly!)

You should configure the sound device to capture audio at typical voice quality rates: 8000 samples/second, 8 bits per sample with one channel (i.e. mono, not stereo).

Read the Rabiner and Sambur paper carefully for details on the algorithm. You should follow it closely. Note, however, that they use a 10kHz sample frequency whereas you will use a 8kHz sample frequency, so adjust your algorithm appropriately.

You are free to add command line options or other features as you like as long as the base functionality as indicated in this writeup is present.


Hints

You can record a fixed chunk of audio data on which to detect silence. For example, you can record sound in 500 ms intervals and then apply the speech detection algorithm to it.

You can use a graphing program to help analyze some of the data you have. If you are using Linux, I'd recommend gnuplot. It has a variety of output and a nice command line interface. You can check out http://www.gnuplot.info/ for a good guide. If you are using a Windows machine, you might use Microsoft Excel. Or, try OpenOffice on any platform.

Here is some coarse pseudo-code for the application that may be helpful:

  open sound device
  set up sound device parameters
  record silence
  set algorithm parameters
  while (1)
     record sound
     compute energy
     compute zero crossings
     search for beginning/end of speech
     write data to file
     write sound to file
     if speech, write speech to file
  end while

You might look at the slides for this project (ppt, pdf) and the [RS75] paper (ppt, pdf).

Windows Implementation

You may do your implementation in Linux or Windows in a language of your choice. This sub-section has some Windows-specific, C++ hints.

To use the sound device, you first create a variable of type WAVEFORMATEX. WAVEFORMATEX is a structure with fields necessary for setting up the sound parameters:

To read from the sound device (e.g. the microphone), you make the system call waveInOpen(), passing in a device handle (HWAVEIN), the device number (1 in the Movie Lab), the WAVEFORMATEX structure above and a callback function. The callback function gets invoked when the sound device has a sample of audio.

As the sound device records information, it needs to be put into a buffer large enough to store the sound chunk (say, 500 ms) you wish to record. You need to create more than one buffer so that the device can read ahead. The buffers are of type LPWAVEHDR. The LPWAVEHDR structure contains lpData, which will record the raw data samples, and dwBufferLength which needs to be set to nBlockAlign (above) times the length (in bytes) of the sound chunk you wish to read from the device.

Once prepared, the LPWAVEHDR buffers are then given one at a time to the sound device via the waveInAddBuffer() system call, giving it the device, the buffer (LPWAVEHDR) and the size of a LPWAVEHDR variable. When the callback function is invoked, the sound data itself will be in the lpData field of the buffer. That data can then be analyzed for speech and written to a file or the audio device (writing to the audio device is very similar to reading from it) or whatever. Another buffer then needs to be added to the audio device via waveInAddBuffer(), again.

Here are some of the header files you will probably find useful:

   #include <windows.h>
   #include <stdio.h>
   #include <stdlib.h>
   #include <mmsystem.h>
   #include <winbase.h>
   #include <memory.h>
   #include <string.h>
   #include <signal.h>
   extern "C"

Here are some data types you will probably use:

   HWAVEOUT /* for writing to an audio device */
   HWAVEIN  /* for reading from the audio device */
   WAVEFORMATEX /* sound format structure */
   LPWAVEHDR /* buffer for reading/writing to device */
   MMRESULT /* result type returned from wave system calls */

You will need to link in the library winmm.lib in order to properly reference the multimedia system calls.

See the online documentation from Visual C++ for more information.

The Microsoft Developer's Network has more elaborate tutorials you can try.

Linux Implementation

You may do your implementation in Linux or Windows in a language of your choice. This sub-section has some Linux-specific hints.

Audio in Linux is typically accessed through the device /dev/dsp. You can open this device for reading and writing as you would a normal file (ie- open("/dev/dsp", O_RDWR). Reading from the device (ie- read() will record sound while writing (ie- write()) to the device will play sound.

You use the ioctl() function to change the device settings (do a man ioctl for more information). The first parameter is the sound device file descriptor, the second is the parameter you want to control and the third is a pointer to a variable containing the value. For example, the code:

   fd = open("/dev/dsp", O_RDWR);
   arg = 8;
   ioctl(fd, SOUND_PCM_WRITE_BITS, &arg);
will set the samples size to 8 bits. The parameters you will be interested in are:

Only one process at a time can have the audio device (/dev/dsp) open. If you get a "permission denied" error when you try to read or write to the audio device, it is likely because another process has it open.

Use a makefile to make compiling easier. Here is a sample (note, the indented lines must be a tab and not spaces):

#
# Makefile for record
#

CC= gcc

all: record

record: record.c
    $(CC) -o record record.c -lm

clean:
    /bin/rm -rf core record


Turn In

You must turn in all source code used in your project, including header files. Please include the project files required for building your code. Have a README file with instructions for building your project and and platform requirements for running your application.

You will use email to turn in your files. When ready, create a directory of your project based on your last name (i.e. claypool) and tar up (with gzip or winzip) your files, for example:

    mkdir claypool
    cp * claypool  // copy all your files to submit to the claypool dir
    tar czvf claypool.tgz claypool

  • Attach your zip file to an email with "cs529-proj1" as the subject.


  • References

    [RS75] L. Rabiner and M. Sambur. An Algorithm for Determining the Endpoints of Isolated Utterances, The Bell System Technical Journal, Vol. 54, No. 2, Feb. 1975, pages 297-315.


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    Send all questions to the Mark Claypool.