WAV audio file handling in SciPy

Introduction

WAV files store sound data. Handling them lets you read, analyze, and save audio in your programs.

You want to read a sound recording to analyze its volume or frequency.

You need to save processed audio after editing or filtering.

You want to convert audio data into numbers for machine learning.

You want to play or visualize sound waves in a project.

You need to extract audio features like duration or sample rate.

Syntax

SciPy

from scipy.io import wavfile

# Read a WAV file
sample_rate, data = wavfile.read('filename.wav')

# Write data to a WAV file
wavfile.write('output.wav', sample_rate, data)

sample_rate is how many samples per second the audio has.

data is a NumPy array with the sound values.

Examples

This reads 'sound.wav' and stores the sample rate and audio data.

SciPy

from scipy.io import wavfile
sample_rate, data = wavfile.read('sound.wav')

This saves the audio data back to a new WAV file.

SciPy

wavfile.write('new_sound.wav', sample_rate, data)

Shows the sample rate and shape of the audio data array.

SciPy

print(f'Sample rate: {sample_rate} Hz')
print(f'Data shape: {data.shape}')

Sample Program

This program reads a WAV file, prints its sample rate, data type, shape, and duration. It also normalizes the audio data if it is stored as integers.

SciPy

from scipy.io import wavfile
import numpy as np

# Read WAV file
sample_rate, data = wavfile.read('example.wav')

# Print basic info
print(f'Sample rate: {sample_rate} Hz')
print(f'Data type: {data.dtype}')
print(f'Data shape: {data.shape}')

# Calculate duration in seconds
duration = data.shape[0] / sample_rate
print(f'Duration: {duration:.2f} seconds')

# Normalize audio data to range -1 to 1 if integer type
if np.issubdtype(data.dtype, np.integer):
    max_val = np.iinfo(data.dtype).max
    min_val = np.iinfo(data.dtype).min
    data_norm = data.astype(np.float32)
    data_norm[data_norm < 0] /= -min_val
    data_norm[data_norm >= 0] /= max_val
    print(f'First 5 normalized samples: {data_norm[:5]}')
else:
    print('Data is not integer type, skipping normalization.')

Important Notes

WAV files can have one (mono) or two (stereo) channels. The data shape changes accordingly.

Normalization helps when you want to process audio values between -1 and 1.

Make sure the WAV file exists in your working folder or provide the full path.

Summary

Use scipy.io.wavfile.read to load WAV audio into arrays.

Use scipy.io.wavfile.write to save arrays back to WAV files.

Check sample rate and data shape to understand your audio file.

Practice

1. What does the function scipy.io.wavfile.read return when you load a WAV audio file?

easy

A. The file size and duration

B. Only the audio data as a list

C. The sample rate and the audio data as a NumPy array

D. The audio format and bit depth

Solution

1. Step 1: Understand the function purpose

   scipy.io.wavfile.read is designed to load WAV files and extract audio information.

2. Step 2: Identify the returned values

   It returns two things: the sample rate (how many samples per second) and the audio data as a NumPy array.

3. Final Answer:

   The sample rate and the audio data as a NumPy array -> Option C

4. Quick Check:

   read() returns (rate, data) [OK]

Hint: Remember read() gives rate and data array [OK]

Common Mistakes:

• Thinking it returns only audio data
• Confusing sample rate with file size
• Expecting metadata like format or bit depth

2. Which of the following is the correct way to import the WAV file reading function from scipy?

easy

A. from scipy.io import wavfile

B. import scipy.wavfile.read

C. from scipy import wavfile.read

D. import wavfile from scipy.io

Solution

1. Step 1: Recall correct import syntax

   Python imports use 'from module import function_or_submodule' format.

2. Step 2: Match with scipy structure

   The correct way is to import the wavfile submodule from scipy.io as from scipy.io import wavfile.

3. Final Answer:

   from scipy.io import wavfile -> Option A

4. Quick Check:

   Correct import syntax = from scipy.io import wavfile [OK]

Hint: Use 'from scipy.io import wavfile' to access read/write [OK]

Common Mistakes:

• Trying to import read directly
• Using dot notation incorrectly in import
• Swapping import order

3. What will be the output shape of the data array when you read a stereo WAV file with 44100 samples per channel using scipy.io.wavfile.read?

medium

A. (88200,)

B. (44100, 2)

C. (44100,)

D. (2, 44100)

Solution

1. Step 1: Understand stereo audio data shape

   Stereo audio has two channels, so data shape is (samples, channels).

2. Step 2: Calculate shape for 44100 samples

   With 44100 samples per channel and 2 channels, shape is (44100, 2).

3. Final Answer:

   (44100, 2) -> Option B

4. Quick Check:

   Stereo shape = (samples, 2) [OK]

Hint: Stereo data shape is (samples, 2) always [OK]

Common Mistakes:

• Confusing channels and samples order
• Assuming shape is (2, samples)
• Thinking stereo data is flattened

4. You try to save a NumPy array with float values using scipy.io.wavfile.write but get an error. What is the likely cause?

medium

A. The file path is incorrect

B. The sample rate is missing

C. The array shape is (samples, 2) instead of (2, samples)

D. The array must be integer type, not float

Solution

1. Step 1: Check data type requirements for write()

   scipy.io.wavfile.write expects integer arrays (e.g., int16) for audio data.

2. Step 2: Identify error cause

   Using float arrays causes errors because WAV format stores integers, so conversion is needed.

3. Final Answer:

   The array must be integer type, not float -> Option D

4. Quick Check:

   write() needs int arrays [OK]

Hint: Convert floats to int before writing WAV [OK]

Common Mistakes:

• Ignoring data type and writing floats directly
• Forgetting sample rate argument
• Misunderstanding array shape requirements

5. You want to double the speed of a WAV audio file using scipy.io.wavfile. Which approach correctly achieves this?

hard

A. Double the sample rate value and write the original data unchanged

B. Read the file, then write only every second sample to a new file

C. Halve the sample rate value and write the original data unchanged

D. Reverse the audio data array and write it with the original sample rate

Solution

1. Step 1: Understand speed and sample rate relation

   Speed changes by adjusting sample rate: doubling sample rate doubles playback speed.

2. Step 2: Apply correct method

   Keep audio data unchanged but write with double the original sample rate to speed up playback.

3. Final Answer:

   Double the sample rate value and write the original data unchanged -> Option A

4. Quick Check:

   Speed ∝ sample rate, double rate doubles speed [OK]

Hint: Change sample rate to speed up audio, not data length [OK]

Common Mistakes:

• Skipping samples instead of changing sample rate
• Halving sample rate to speed up (actually slows down)
• Reversing data does not change speed