Harika Basana ([email protected] ), Elizabeth Chan ([email protected] ), Nikolai Sinkov([email protected] ), Frank Zhang ([email protected] ) 6100 Main Street, Rice University, Houston, Texas 77005
- To explore the MP3 technology and
- to implement various audio data compression
- Analyze This
- Audio compression is to compress an audio
file into a smaller-sized file.
- People cannot differentiate between these
two files by just hearing.
- Due to its smaller size, the new file can be easily
transferred via the Internet.
- People try to find better audio compression
algorithms that retain satisfying audio quality.
Ding.wav before compression
Ding.wav with frequencies within 1 std from the mean
Original signal sampled at 44100Hz
The x-axis DT sample and the y-axis is the amplitude
After linear quantization
Ding.wav with frequencies within 2 std from the mean
Ding.wav with frequencies within 3 std from the mean
After tangent quantization
After arctangent quantization
- Masking Algorithm
- The presence of a signal at a particular frequency can
- raise the perceptual threshold of signals close to the
- the masking frequency.
- Go through every sample and remove the following
samples if they are below a certain threshold.
- No significant improvement. Need a better way of
implementing to get good results.
- Average Energy Algorithm
- Zeroes out selected high and low frequencies of
- the audio file.
- Perform the Discrete Cosine Transform (DCT).
- Calculate the signal’s energy.
- Find the mean and the standard deviation of
from the energy spectrum.
- Keep all frequencies with energies within 1
standard deviation (std) from the mean.
- Zero out frequencies with energies outside this range.
- Similarly, keep frequencies with energies within 2
and 3 stds from the mean.
- Perform the Inverse DCT and get the output.
- Amount of compression is insignificant.
- Algorithm would probably work better if the signal
is very short, has monotonous tones, and has little
- Psycho Acoustic Algorithm
- Linear, tangent or arctangent quantization of the
- Perform the Discrete Cosine Transform (DCT)
- Quantize the signal in one of the following ways :
Diagram of the quantization “buckets” for the three
- Give certain frequency bands more bits
(1000 – 5100 Hz and 12500 - 15200Hz).
- Throw away frequencies below 20Hz and above
- Compression is very significant.
- Quality is good for the amount of compression.
- Arctangent quantization yields the best quality.
- We didn’t create MP3 files.
- Used the underlying concepts.
- Produced much smaller files.
- Psycho Acoustic Algorithm is the best, in terms of
- amount of compression
- sound quality of the output.
- Implement windowing
- Implement temporal masking
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