sip-assign2
May 7, 2025
ASSIGNMENT2
[5]: from google.colab import drive
drive.mount('/content/drive')
--------------------------------------------------------------------------ValueError
Traceback (most recent call last)
<ipython-input-5-d5df0069828e> in <cell line: 0>()
1 from google.colab import drive
----> 2 drive.mount('/content/drive')
/usr/local/lib/python3.11/dist-packages/google/colab/drive.py in␣
↪mount(mountpoint, force_remount, timeout_ms, readonly)
98 def mount(mountpoint, force_remount=False, timeout_ms=120000,␣
↪readonly=False):
99
"""Mount your Google Drive at the specified mountpoint path."""
--> 100
return _mount(
101
102
mountpoint,
force_remount=force_remount,
/usr/local/lib/python3.11/dist-packages/google/colab/drive.py in␣
↪_mount(mountpoint, force_remount, timeout_ms, ephemeral, readonly)
197
raise ValueError('Mountpoint must not be a symlink')
198
if _os.path.isdir(mountpoint) and _os.listdir(mountpoint):
--> 199
raise ValueError('Mountpoint must not already contain files')
200
if not _os.path.isdir(mountpoint) and _os.path.exists(mountpoint):
201
raise ValueError('Mountpoint must either be a directory or not␣
↪exist')
ValueError: Mountpoint must not already contain files
QUESTION 1
[7]: import os
import numpy as np
import matplotlib.pyplot as plt
import scipy.signal as signal
1
import soundfile as sf
import pandas as pd
from tabulate import tabulate
import time
def create_directories(base_dir, output_dir):
os.makedirs(output_dir, exist_ok=True)
print(f"Output directory: {output_dir}")
return output_dir
def list_audio_files(directory, extension='.wav'):
return [f for f in os.listdir(directory) if f.endswith(extension)]
def design_band_stop_filter(samples, fs, low_freq, high_freq):
nyquist = 0.5 * fs
norm_low = low_freq / nyquist
norm_high = high_freq / nyquist
if norm_high >= 1.0:
norm_high = 0.99
if norm_low >= norm_high:
print(f"Invalid filter: low={low_freq:.2f} Hz, high={high_freq:.2f} Hz")
return samples
b, a = signal.butter(2, [norm_low, norm_high], btype='bandstop')
try:
filtered_audio = signal.filtfilt(b, a, samples, padtype='odd', padlen=3)
except ValueError:
print(f"Warning: Using lfilter for {low_freq}-{high_freq}Hz")
filtered_audio = signal.lfilter(b, a, samples)
return filtered_audio
def process_audio_files(source_dir, dest_dir, sample_rate, freq_range):
audio_files = list_audio_files(source_dir)
if not audio_files:
print(f"No audio files found in {source_dir}")
return {}
quality_ratings = {}
for audio_file in audio_files:
print(f"\n{'='*50}\nProcessing: {audio_file}")
file_path = os.path.join(source_dir, audio_file)
2
audio_samples, actual_sample_rate = sf.read(file_path)
duration = len(audio_samples)/actual_sample_rate
print(f"Audio: {len(audio_samples)} samples, {duration:.2f} seconds")
quality_ratings[audio_file] = {}
for center_freq in freq_range:
high_freq = center_freq + 1000
filtered_audio = design_band_stop_filter(
audio_samples, actual_sample_rate, center_freq, high_freq
)
output_filename = f"{os.path.
↪splitext(audio_file)[0]}_notch_{int(center_freq)}-{int(high_freq)}Hz.wav"
output_path = os.path.join(dest_dir, output_filename)
sf.write(output_path, filtered_audio, actual_sample_rate)
print(f"\nFiltered: {center_freq}Hz - {high_freq}Hz")
print(f"Original: '{audio_file}' | Filtered: '{output_filename}'")
while True:
try:
quality_rating = int(input(f"Rate quality (0=different,␣
↪10=identical): "))
if 0 <= quality_rating <= 10:
break
else:
print("Enter 0-10")
except ValueError:
print("Invalid input")
quality_ratings[audio_file][center_freq] = quality_rating
return quality_ratings
def display_rating_table(ratings, freq_range):
df = pd.DataFrame(index=ratings.keys(),␣
↪columns=[f"{int(f)}-{int(f+1000)}Hz" for f in freq_range])
for file, file_ratings in ratings.items():
for freq, rating in file_ratings.items():
df.loc[file, f"{int(freq)}-{int(freq+1000)}Hz"] = rating
df.loc['Average'] = df.mean(numeric_only=True)
print("\n\nAudio Quality Ratings (higher is better):")
print(tabulate(df, headers='keys', tablefmt='grid', showindex=True))
3
timestamp = time.strftime("%Y%m%d-%H%M%S")
csv_filename = f"quality_ratings_{timestamp}.csv"
df.to_csv(csv_filename)
print(f"\nRatings saved to {csv_filename}")
return df
def plot_ratings(ratings_df, output_dir):
df_without_avg = ratings_df.drop('Average', errors='ignore')
plt.figure(figsize=(12, 8))
for file in df_without_avg.index:
freqs = [int(col.split('-')[0]) for col in ratings_df.columns]
plt.plot(freqs, df_without_avg.loc[file], marker='o', label=file)
plt.plot(freqs, ratings_df.loc['Average'], 'k--', linewidth=2,␣
label='Average')
↪
plt.xlabel('Center Frequency (Hz)')
plt.ylabel('Quality Rating')
plt.title('Audio Quality Ratings by Frequency Band')
plt.grid(True)
plt.legend()
plt.tight_layout()
plot_filename = os.path.join(output_dir, 'quality_ratings_plot.png')
plt.savefig(plot_filename)
print(f"Plot saved to {plot_filename}")
plt.close()
def main():
source_directory = "/content/que1"
destination_directory = "/content/drive/MyDrive/sip_assign_2que_1"
sampling_rate = 16000
student_id = 9578956
print(f"Student ID: {student_id}")
freq_increment = 500
lower_freq = 500
upper_freq = 7000
frequency_range = np.arange(lower_freq, upper_freq + freq_increment,␣
↪freq_increment)
output_dir = create_directories(source_directory, destination_directory)
4
ratings = process_audio_files(source_directory, output_dir, sampling_rate,␣
frequency_range)
ratings_df = display_rating_table(ratings, frequency_range)
plot_ratings(ratings_df, output_dir)
↪
print("\nAudio processing complete!")
if __name__ == "__main__":
main()
Student ID: 9578956
Output directory: /content/drive/MyDrive/sip_assign_2que_1
==================================================
Processing: Speaker_3.wav
Audio: 190464 samples, 4.32 seconds
Warning: Using lfilter for 500-1500Hz
Filtered: 500Hz - 1500Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_500-1500Hz.wav'
Rate quality (0=different, 10=identical): 7
Warning: Using lfilter for 1000-2000Hz
Filtered: 1000Hz - 2000Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_1000-2000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 1500-2500Hz
Filtered: 1500Hz - 2500Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_1500-2500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 2000-3000Hz
Filtered: 2000Hz - 3000Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_2000-3000Hz.wav'
Rate quality (0=different, 10=identical): 7
Warning: Using lfilter for 2500-3500Hz
Filtered: 2500Hz - 3500Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_2500-3500Hz.wav'
Rate quality (0=different, 10=identical): 6
Warning: Using lfilter for 3000-4000Hz
Filtered: 3000Hz - 4000Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_3000-4000Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 3500-4500Hz
5
Filtered: 3500Hz - 4500Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_3500-4500Hz.wav'
Rate quality (0=different, 10=identical): 5
Warning: Using lfilter for 4000-5000Hz
Filtered: 4000Hz - 5000Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_4000-5000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 4500-5500Hz
Filtered: 4500Hz - 5500Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_4500-5500Hz.wav'
Rate quality (0=different, 10=identical): 5
Warning: Using lfilter for 5000-6000Hz
Filtered: 5000Hz - 6000Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_5000-6000Hz.wav'
Rate quality (0=different, 10=identical): 6
Warning: Using lfilter for 5500-6500Hz
Filtered: 5500Hz - 6500Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_5500-6500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 6000-7000Hz
Filtered: 6000Hz - 7000Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_6000-7000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 6500-7500Hz
Filtered: 6500Hz - 7500Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_6500-7500Hz.wav'
Rate quality (0=different, 10=identical): 6
Warning: Using lfilter for 7000-8000Hz
Filtered: 7000Hz - 8000Hz
Original: 'Speaker_3.wav' | Filtered: 'Speaker_3_notch_7000-8000Hz.wav'
Rate quality (0=different, 10=identical): 8
==================================================
Processing: Speaker_2.wav
Audio: 194745 samples, 4.42 seconds
Warning: Using lfilter for 500-1500Hz
Filtered: 500Hz - 1500Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_500-1500Hz.wav'
Rate quality (0=different, 10=identical): 7
6
Warning: Using lfilter for 1000-2000Hz
Filtered: 1000Hz - 2000Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_1000-2000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 1500-2500Hz
Filtered: 1500Hz - 2500Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_1500-2500Hz.wav'
Rate quality (0=different, 10=identical): 5
Warning: Using lfilter for 2000-3000Hz
Filtered: 2000Hz - 3000Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_2000-3000Hz.wav'
Rate quality (0=different, 10=identical): 7
Warning: Using lfilter for 2500-3500Hz
Filtered: 2500Hz - 3500Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_2500-3500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 3000-4000Hz
Filtered: 3000Hz - 4000Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_3000-4000Hz.wav'
Rate quality (0=different, 10=identical): 5
Warning: Using lfilter for 3500-4500Hz
Filtered: 3500Hz - 4500Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_3500-4500Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 4000-5000Hz
Filtered: 4000Hz - 5000Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_4000-5000Hz.wav'
Rate quality (0=different, 10=identical): 4
Warning: Using lfilter for 4500-5500Hz
Filtered: 4500Hz - 5500Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_4500-5500Hz.wav'
Rate quality (0=different, 10=identical): 7
Warning: Using lfilter for 5000-6000Hz
Filtered: 5000Hz - 6000Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_5000-6000Hz.wav'
Rate quality (0=different, 10=identical): 5
Warning: Using lfilter for 5500-6500Hz
Filtered: 5500Hz - 6500Hz
7
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_5500-6500Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 6000-7000Hz
Filtered: 6000Hz - 7000Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_6000-7000Hz.wav'
Rate quality (0=different, 10=identical): 10
Warning: Using lfilter for 6500-7500Hz
Filtered: 6500Hz - 7500Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_6500-7500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 7000-8000Hz
Filtered: 7000Hz - 8000Hz
Original: 'Speaker_2.wav' | Filtered: 'Speaker_2_notch_7000-8000Hz.wav'
Rate quality (0=different, 10=identical): 7
==================================================
Processing: Speaker_4.wav
Audio: 159744 samples, 3.62 seconds
Warning: Using lfilter for 500-1500Hz
Filtered: 500Hz - 1500Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_500-1500Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 1000-2000Hz
Filtered: 1000Hz - 2000Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_1000-2000Hz.wav'
Rate quality (0=different, 10=identical): 6
Warning: Using lfilter for 1500-2500Hz
Filtered: 1500Hz - 2500Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_1500-2500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 2000-3000Hz
Filtered: 2000Hz - 3000Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_2000-3000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 2500-3500Hz
Filtered: 2500Hz - 3500Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_2500-3500Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 3000-4000Hz
8
Filtered: 3000Hz - 4000Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_3000-4000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 3500-4500Hz
Filtered: 3500Hz - 4500Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_3500-4500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 4000-5000Hz
Filtered: 4000Hz - 5000Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_4000-5000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 4500-5500Hz
Filtered: 4500Hz - 5500Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_4500-5500Hz.wav'
Rate quality (0=different, 10=identical): 6
Warning: Using lfilter for 5000-6000Hz
Filtered: 5000Hz - 6000Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_5000-6000Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 5500-6500Hz
Filtered: 5500Hz - 6500Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_5500-6500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 6000-7000Hz
Filtered: 6000Hz - 7000Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_6000-7000Hz.wav'
Rate quality (0=different, 10=identical): 10
Warning: Using lfilter for 6500-7500Hz
Filtered: 6500Hz - 7500Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_6500-7500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 7000-8000Hz
Filtered: 7000Hz - 8000Hz
Original: 'Speaker_4.wav' | Filtered: 'Speaker_4_notch_7000-8000Hz.wav'
Rate quality (0=different, 10=identical): 8
==================================================
Processing: Speaker_5.wav
Audio: 256216 samples, 5.34 seconds
9
Filtered: 500Hz - 1500Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_500-1500Hz.wav'
Rate quality (0=different, 10=identical): 8
Filtered: 1000Hz - 2000Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_1000-2000Hz.wav'
Rate quality (0=different, 10=identical): 9
Filtered: 1500Hz - 2500Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_1500-2500Hz.wav'
Rate quality (0=different, 10=identical): 6
Filtered: 2000Hz - 3000Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_2000-3000Hz.wav'
Rate quality (0=different, 10=identical): 6
Filtered: 2500Hz - 3500Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_2500-3500Hz.wav'
Rate quality (0=different, 10=identical): 9
Filtered: 3000Hz - 4000Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_3000-4000Hz.wav'
Rate quality (0=different, 10=identical): 5
Filtered: 3500Hz - 4500Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_3500-4500Hz.wav'
Rate quality (0=different, 10=identical): 8
Filtered: 4000Hz - 5000Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_4000-5000Hz.wav'
Rate quality (0=different, 10=identical): 8
Filtered: 4500Hz - 5500Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_4500-5500Hz.wav'
Rate quality (0=different, 10=identical): 7
Filtered: 5000Hz - 6000Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_5000-6000Hz.wav'
Rate quality (0=different, 10=identical): 7
Filtered: 5500Hz - 6500Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_5500-6500Hz.wav'
Rate quality (0=different, 10=identical): 10
Filtered: 6000Hz - 7000Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_6000-7000Hz.wav'
Rate quality (0=different, 10=identical): 7
10
Filtered: 6500Hz - 7500Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_6500-7500Hz.wav'
Rate quality (0=different, 10=identical): 8
Filtered: 7000Hz - 8000Hz
Original: 'Speaker_5.wav' | Filtered: 'Speaker_5_notch_7000-8000Hz.wav'
Rate quality (0=different, 10=identical): 8
==================================================
Processing: Speaker_1.wav
Audio: 144384 samples, 3.27 seconds
Warning: Using lfilter for 500-1500Hz
Filtered: 500Hz - 1500Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_500-1500Hz.wav'
Rate quality (0=different, 10=identical): 7
Warning: Using lfilter for 1000-2000Hz
Filtered: 1000Hz - 2000Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_1000-2000Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 1500-2500Hz
Filtered: 1500Hz - 2500Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_1500-2500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 2000-3000Hz
Filtered: 2000Hz - 3000Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_2000-3000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 2500-3500Hz
Filtered: 2500Hz - 3500Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_2500-3500Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 3000-4000Hz
Filtered: 3000Hz - 4000Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_3000-4000Hz.wav'
Rate quality (0=different, 10=identical): 6
Warning: Using lfilter for 3500-4500Hz
Filtered: 3500Hz - 4500Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_3500-4500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 4000-5000Hz
11
Filtered: 4000Hz - 5000Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_4000-5000Hz.wav'
Rate quality (0=different, 10=identical): 6
Warning: Using lfilter for 4500-5500Hz
Filtered: 4500Hz - 5500Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_4500-5500Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 5000-6000Hz
Filtered: 5000Hz - 6000Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_5000-6000Hz.wav'
Rate quality (0=different, 10=identical): 9
Warning: Using lfilter for 5500-6500Hz
Filtered: 5500Hz - 6500Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_5500-6500Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 6000-7000Hz
Filtered: 6000Hz - 7000Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_6000-7000Hz.wav'
Rate quality (0=different, 10=identical): 8
Warning: Using lfilter for 6500-7500Hz
Filtered: 6500Hz - 7500Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_6500-7500Hz.wav'
Rate quality (0=different, 10=identical): 7
Warning: Using lfilter for 7000-8000Hz
Filtered: 7000Hz - 8000Hz
Original: 'Speaker_1.wav' | Filtered: 'Speaker_1_notch_7000-8000Hz.wav'
Rate quality (0=different, 10=identical): 6
Audio Quality Ratings (higher is better):
+---------------+--------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
|
|
500-1500Hz |
1000-2000Hz |
1500-2500Hz |
2000-3000Hz |
2500-3500Hz |
3000-4000Hz |
3500-4500Hz |
4000-5000Hz |
4500-5500Hz |
5000-6000Hz |
5500-6500Hz |
6000-7000Hz |
6500-7500Hz |
7000-8000Hz |
+===============+==============+===============+===============+===============+
===============+===============+===============+===============+===============+
===============+===============+===============+===============+===============+
| Speaker_3.wav |
7 |
9 |
8 |
7 |
6 |
8 |
5 |
9 |
5 |
6 |
8 |
9 |
6 |
8 |
12
+---------------+--------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
7 |
5 |
| Speaker_2.wav |
9 |
7 |
8 |
5 |
9 |
4 |
7 |
5 |
9 |
10 |
8 |
7 |
+---------------+--------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
| Speaker_4.wav |
9 |
6 |
8 |
9 |
9 |
9 |
8 |
9 |
6 |
8 |
8 |
10 |
8 |
8 |
+---------------+--------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
| Speaker_5.wav |
8 |
9 |
6 |
6 |
9 |
5 |
8 |
8 |
7 |
7 |
10 |
7 |
8 |
8 |
+---------------+--------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
| Speaker_1.wav |
7 |
8 |
8 |
9 |
9 |
6 |
8 |
6 |
9 |
9 |
8 |
8 |
7 |
6 |
+---------------+--------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
| Average
|
nan |
nan |
nan |
nan |
nan |
nan |
nan |
nan |
nan |
nan |
nan |
nan |
nan |
nan |
+---------------+--------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
---------------+---------------+---------------+---------------+---------------+
Ratings saved to quality_ratings_20250507-104701.csv
Plot saved to /content/drive/MyDrive/sip_assign_2que_1/quality_ratings_plot.png
Audio processing complete!
Summary of Findings The experiment investigated the perceptual effects of bandstop filtering on
speech recordings by applying filters with a 1000Hz bandwidth at various center frequencies. Five
speakers’ recordings were evaluated, and quality ratings were assigned on a scale of 0-10 (where
10 indicates no perceptible difference between filtered and original recordings). Best Performing
Frequency Bands The analysis revealed that different frequency bands yielded optimal results for
different speakers:
Speaker 1: 2000-3000Hz and 2500-3500Hz (tied at score 9)
Speaker 2: 6000-7000Hz (score 10)
13
Speaker 3: 1000-2000Hz and 4000-5000Hz (tied at score 9)
Speaker 4: 6000-7000Hz (score 10)
Speaker 5: 5500-6500Hz (score 10)
Overall Performance Analysis
The highest average score across all speakers was achieved by the 6000-7000Hz band (8.80) Two
speakers had their best performance with the 6000-7000Hz bandstop filter The overall average
quality score was 7.57
QUESTION 2
QUESTION 3
[ ]: import matplotlib.pyplot as plt
import collections
import seaborn as sns
[ ]: def read_dict(fpath):
phon_dict = {}
with open(fpath, 'r', encoding='latin1') as file:
for line in file:
if line.startswith(';;;'):
continue
parts = line.strip().split()
phon_dict[parts[0]] = parts[1:]
return phon_dict
[ ]: def draw_cumulative_chart(phon_dict):
lengths = [len(phns) for phns in phon_dict.values()]
max_len = 30
counts = [sum(1 for ln in lengths if ln <= k) for k in range(1, max_len +␣
↪1)]
sns.set_style("whitegrid")
plt.figure(figsize=(8, 5))
sns.lineplot(x=range(1, max_len + 1), y=counts, marker='o', linewidth=2)
plt.xlabel('Max Phoneme Length', fontsize=12)
plt.ylabel('Cumulative Word Count', fontsize=12)
plt.title('Cumulative Count of Words by Phoneme Length', fontsize=14)
plt.show()
[ ]: def draw_phoneme_bar_chart(phon_dict):
phoneme_freq = collections.Counter()
14
for phns in phon_dict.values():
phoneme_freq.update(phns)
phon_list, freq_list = zip(*phoneme_freq.items())
sns.set_style("whitegrid")
plt.figure(figsize=(12, 6))
sns.barplot(x=list(phon_list), y=list(freq_list), palette="viridis")
plt.xlabel('Phoneme', fontsize=12)
plt.ylabel('Frequency', fontsize=12)
plt.title('Phoneme Frequency Distribution', fontsize=14)
plt.xticks(rotation=90)
plt.show()
[ ]: def extract_phonemes(sentence, phon_dict):
return [phon_dict.get(word, ['UNKNOWN']) for word in sentence.upper().
↪split()]
[ ]: def count_matching_lengths(phon_dict):
return sum(1 for word, phns in phon_dict.items() if len(word) == len(phns))
[ ]: phoneme_dict = read_dict('cmudict-0.7b.txt')
draw_cumulative_chart(phoneme_dict)
draw_phoneme_bar_chart(phoneme_dict)
print("Phonemic sequence:", extract_phonemes("Hello world", phoneme_dict))
print("Words where word length == phoneme length:",␣
↪count_matching_lengths(phoneme_dict))
15
<ipython-input-4-6086b7fb4467>:8: FutureWarning:
Passing `palette` without assigning `hue` is deprecated and will be removed in
v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same
effect.
sns.barplot(x=list(phon_list), y=list(freq_list), palette="viridis")
Phonemic sequence: [['HH', 'AH0', 'L', 'OW1'], ['W', 'ER1', 'L', 'D']]
Words where word length == phoneme length: 32222
QUESTION 4
[ ]: !pip install g2p-en torch
Requirement already satisfied: g2p-en in /usr/local/lib/python3.11/dist-packages
(2.1.0)
Requirement already satisfied: torch in /usr/local/lib/python3.11/dist-packages
(2.5.1+cu124)
Requirement already satisfied: numpy>=1.13.1 in /usr/local/lib/python3.11/distpackages (from g2p-en) (1.26.4)
Requirement already satisfied: nltk>=3.2.4 in /usr/local/lib/python3.11/distpackages (from g2p-en) (3.9.1)
Requirement already satisfied: inflect>=0.3.1 in /usr/local/lib/python3.11/distpackages (from g2p-en) (7.5.0)
Requirement already satisfied: distance>=0.1.3 in
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/usr/local/lib/python3.11/dist-packages (from g2p-en) (0.1.3)
Requirement already satisfied: filelock in /usr/local/lib/python3.11/distpackages (from torch) (3.17.0)
Requirement already satisfied: typing-extensions>=4.8.0 in
/usr/local/lib/python3.11/dist-packages (from torch) (4.12.2)
Requirement already satisfied: networkx in /usr/local/lib/python3.11/distpackages (from torch) (3.4.2)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages
(from torch) (3.1.5)
Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages
(from torch) (2024.10.0)
Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in
/usr/local/lib/python3.11/dist-packages (from torch) (12.4.127)
Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in
/usr/local/lib/python3.11/dist-packages (from torch) (12.4.127)
Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in
/usr/local/lib/python3.11/dist-packages (from torch) (12.4.127)
Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in
/usr/local/lib/python3.11/dist-packages (from torch) (9.1.0.70)
Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in
/usr/local/lib/python3.11/dist-packages (from torch) (12.4.5.8)
Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in
/usr/local/lib/python3.11/dist-packages (from torch) (11.2.1.3)
Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in
/usr/local/lib/python3.11/dist-packages (from torch) (10.3.5.147)
Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in
/usr/local/lib/python3.11/dist-packages (from torch) (11.6.1.9)
Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in
/usr/local/lib/python3.11/dist-packages (from torch) (12.3.1.170)
Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in
/usr/local/lib/python3.11/dist-packages (from torch) (2.21.5)
Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in
/usr/local/lib/python3.11/dist-packages (from torch) (12.4.127)
Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in
/usr/local/lib/python3.11/dist-packages (from torch) (12.4.127)
Requirement already satisfied: triton==3.1.0 in /usr/local/lib/python3.11/distpackages (from torch) (3.1.0)
Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/distpackages (from torch) (1.13.1)
Requirement already satisfied: mpmath<1.4,>=1.1.0 in
/usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch) (1.3.0)
Requirement already satisfied: more_itertools>=8.5.0 in
/usr/local/lib/python3.11/dist-packages (from inflect>=0.3.1->g2p-en) (10.6.0)
Requirement already satisfied: typeguard>=4.0.1 in
/usr/local/lib/python3.11/dist-packages (from inflect>=0.3.1->g2p-en) (4.4.2)
Requirement already satisfied: click in /usr/local/lib/python3.11/dist-packages
(from nltk>=3.2.4->g2p-en) (8.1.8)
Requirement already satisfied: joblib in /usr/local/lib/python3.11/dist-packages
17
(from nltk>=3.2.4->g2p-en) (1.4.2)
Requirement already satisfied: regex>=2021.8.3 in
/usr/local/lib/python3.11/dist-packages (from nltk>=3.2.4->g2p-en) (2024.11.6)
Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages
(from nltk>=3.2.4->g2p-en) (4.67.1)
Requirement already satisfied: MarkupSafe>=2.0 in
/usr/local/lib/python3.11/dist-packages (from jinja2->torch) (3.0.2)
[ ]: nltk.download('cmudict')
nltk.download('punkt')
[nltk_data] Downloading package cmudict to /root/nltk_data…
[nltk_data]
Package cmudict is already up-to-date!
[nltk_data] Downloading package punkt to /root/nltk_data…
[nltk_data]
Package punkt is already up-to-date!
[ ]: True
[ ]: import nltk
nltk.download('averaged_perceptron_tagger')
nltk.download('cmudict')
nltk.download('punkt')
nltk.download('maxent_ne_chunker')
nltk.download('words')
[nltk_data] Downloading package averaged_perceptron_tagger to
[nltk_data]
/root/nltk_data…
[nltk_data]
Package averaged_perceptron_tagger is already up-to[nltk_data]
date!
[nltk_data] Downloading package cmudict to /root/nltk_data…
[nltk_data]
Package cmudict is already up-to-date!
[nltk_data] Downloading package punkt to /root/nltk_data…
[nltk_data]
Package punkt is already up-to-date!
[nltk_data] Downloading package maxent_ne_chunker to
[nltk_data]
/root/nltk_data…
[nltk_data]
Package maxent_ne_chunker is already up-to-date!
[nltk_data] Downloading package words to /root/nltk_data…
[nltk_data]
Package words is already up-to-date!
[ ]: True
[ ]: import nltk
nltk.download('averaged_perceptron_tagger_eng')
nltk.download('cmudict')
[nltk_data] Downloading package averaged_perceptron_tagger_eng to
[nltk_data]
/root/nltk_data…
[nltk_data]
Unzipping taggers/averaged_perceptron_tagger_eng.zip.
18
[nltk_data] Downloading package cmudict to /root/nltk_data…
[nltk_data]
Package cmudict is already up-to-date!
[ ]: True
[ ]: !pip install --upgrade nltk
Requirement already satisfied: nltk in /usr/local/lib/python3.11/dist-packages
(3.9.1)
Requirement already satisfied: click in /usr/local/lib/python3.11/dist-packages
(from nltk) (8.1.8)
Requirement already satisfied: joblib in /usr/local/lib/python3.11/dist-packages
(from nltk) (1.4.2)
Requirement already satisfied: regex>=2021.8.3 in
/usr/local/lib/python3.11/dist-packages (from nltk) (2024.11.6)
Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages
(from nltk) (4.67.1)
[ ]: from g2p_en import G2p
g2p = G2p()
words = [
"wonderfully", "magnificent", "experience", "understand", "incredible",
"opportunity", "successful", "university", "enthusiastic", "appreciation"
]
phoneme_sequences = {w: g2p(w) for w in words}
for word, phonemes in phoneme_sequences.items():
print(f"{word}: {' '.join(phonemes)}")
wonderfully: W AH1 N D ER0 F AH0 L IY0
magnificent: M AE0 G N IH1 F AH0 S AH0 N T
experience: IH0 K S P IH1 R IY0 AH0 N S
understand: AH2 N D ER0 S T AE1 N D
incredible: IH0 N K R EH1 D AH0 B AH0 L
opportunity: AA2 P ER0 T UW1 N AH0 T IY0
successful: S AH0 K S EH1 S F AH0 L
university: Y UW2 N AH0 V ER1 S AH0 T IY0
enthusiastic: IH0 N TH UW2 Z IY0 AE1 S T IH0 K
appreciation: AH0 P R IY2 SH IY0 EY1 SH AH0 N
Question 6
[ ]: import numpy as np
import librosa
import librosa.display
19
import scipy.signal as sig
import matplotlib.pyplot as plt
import os
[ ]: def calc_ltas(audio_file, win_dur=0.02, sample_rate=16000, fft_size=1024):
audio_data, sr = librosa.load(audio_file, sr=sample_rate)
frame_len = int(win_dur * sr)
freqs, power_spec = sig.welch(audio_data, fs=sr, nperseg=frame_len,␣
↪nfft=fft_size)
log_power = 10 * np.log10(power_spec + 1e-10)
return freqs, log_power
[ ]: def visualize_ltas(freq_vals, ltas_collection, legends, graph_title):
plt.figure(figsize=(10, 5))
for spectrum, legend in zip(ltas_collection, legends):
plt.plot(freq_vals, spectrum, label=legend, linewidth=2)
plt.xlabel("Frequency (Hz)")
plt.ylabel("Power (dB)")
plt.title(graph_title)
plt.grid(True)
plt.legend()
plt.show()
[ ]: speech_files = [
"/content/q5_recording/RecordingFilename_Avish_Fakirde_Group1.wav", "/
↪content/q5_recording/RecordingFilename_Avish_Fakirde_Group2.wav",
"/content/q5_recording/RecordingFilename_Avish_Fakirde_Group3.wav", "/
↪content/q5_recording/RecordingFilename_Avish_Fakirde_Group4.wav",
"/content/q5_recording/RecordingFilename_Avish_Fakirde_Group5.wav", "/
↪content/q5_recording/RecordingFilename_Avish_Fakirde_Group6.wav"
]
noise_files = [
"/content/q5_noise/street-and-traffic-ambience-london-52033.wav", "/content/
↪q5_noise/the-rain-and-the-city-traffic-190469.wav",
"/content/q5_noise/indian-wedding-dhols-52474.wav",
"/content/q5_noise/flea-market-ambience-hungary-19196.wav"
]
speech_ltas, noise_ltas = [], []
labels_speech, labels_noise = [], []
[ ]: for idx, clip in enumerate(speech_files):
if os.path.exists(clip):
freq_vals, spectrum = calc_ltas(clip)
speech_ltas.append(spectrum)
20
labels_speech.append(f"Speech {idx+1}")
for idx, clip in enumerate(noise_files):
if os.path.exists(clip):
_, spectrum = calc_ltas(clip)
noise_ltas.append(spectrum)
labels_noise.append(f"Noise {idx+1}")
visualize_ltas(freq_vals, speech_ltas, labels_speech, "LTAS - Speech␣
↪Recordings")
visualize_ltas(freq_vals, noise_ltas, labels_noise, "LTAS - Noise Recordings")
for idx, noise_spectrum in enumerate(noise_ltas):
combined_spectra = speech_ltas + [noise_spectrum]
combined_labels = labels_speech + [labels_noise[idx]]
visualize_ltas(freq_vals, combined_spectra, combined_labels, f"LTAS -␣
↪Speech vs {labels_noise[idx]}")
21
22
23
[ ]: def closest_ltas_match(speech_data, noise_data):
min_diff = float("inf")
best_match = None
for noise_idx, noise_spec in enumerate(noise_data):
for speech_idx, speech_spec in enumerate(speech_data):
diff = np.linalg.norm(noise_spec - speech_spec)
if diff < min_diff:
min_diff = diff
best_match = (noise_idx, speech_idx)
return best_match
[ ]: matched_noise, matched_speech = closest_ltas_match(speech_ltas, noise_ltas)
print(f"Most Similar LTAS: Speech {matched_speech+1} � Noise {matched_noise+1}")
Most Similar LTAS: Speech 2 � Noise 4
NOISE 4 THAT IS MARKET NOISE IS MATCHING
QUESTION 5
[ ]: !pip install praat-parselmouth
Collecting praat-parselmouth
Downloading praat_parselmouth-0.4.5-cp311-cp311-manylinux_2_17_x86_64.manylinu
x2014_x86_64.whl.metadata (2.9 kB)
Requirement already satisfied: numpy>=1.7.0 in /usr/local/lib/python3.11/distpackages (from praat-parselmouth) (2.0.2)
Downloading praat_parselmouth-0.4.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2
014_x86_64.whl (10.8 MB)
24
���������������������������������������� 10.8/10.8 MB
89.1 MB/s eta 0:00:00
Installing collected packages: praat-parselmouth
Successfully installed praat-parselmouth-0.4.5
[ ]: import os
import numpy as np
import librosa
import librosa.display
import scipy.signal
import scipy.fftpack
import scipy.io.wavfile as wav
import parselmouth
def formant_vals(x):
y = parselmouth.Sound(x)
z = y.to_formant_burg(time_step=0.01, max_number_of_formants=5)
a1, a2, a3 = [], [], []
for b in np.arange(0, y.duration, 0.01):
p = z.get_value_at_time(1, b)
q = z.get_value_at_time(2, b)
r = z.get_value_at_time(3, b)
if p and q and r:
a1.append(p)
a2.append(q)
a3.append(r)
return np.mean(a1), np.mean(a2), np.mean(a3)
def freq_shift(u, v, src_f, tgt_f):
s1, s2, s3 = src_f
t1, t2, t3 = tgt_f
g = np.fft.rfft(u)
h = np.fft.rfftfreq(len(u), d=1/v)
def remap(k):
if k < s1:
return k * (t1 / s1)
elif k < s2:
return k * (t2 / s2)
elif k < s3:
return k * (t3 / s3)
else:
return k
new_g = np.zeros_like(g, dtype=complex)
for i, j in enumerate(h):
m = remap(j)
idx = np.argmin(np.abs(h - m))
new_g[idx] = g[i]
25
z = np.fft.irfft(new_g)
return z
in_dir = "/content/q5_input"
out_dir = "/content/drive/MyDrive/sip_assign_2que_5"
os.makedirs(out_dir, exist_ok=True)
files = [f for f in os.listdir(in_dir) if f.endswith(".wav")]
f_vals = {}
for f in files:
p = os.path.join(in_dir, f)
f_vals[f] = formant_vals(p)
for s in files:
s_path = os.path.join(in_dir, s)
rate, audio = wav.read(s_path)
audio = audio.astype(np.float32)
for t in files:
if s == t:
continue
tgt_f = f_vals[t]
mod_audio = freq_shift(audio, rate, f_vals[s], tgt_f)
name = f"{s[:-4]}_to_{t}"
save_path = os.path.join(out_dir, name + ".wav")
wav.write(save_path, rate, mod_audio.astype(np.int16))
print(f"Converted {s} → {t} and saved to {save_path}")
print("All vowel transformations completed!")
Converted IY.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_O.wav.wav
Converted IY.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_AE.wav.wav
Converted IY.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_ER.wav.wav
Converted IY.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_I.wav.wav
Converted IY.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_UH.wav.wav
Converted IY.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_AH.wav.wav
Converted IY.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_OW.wav.wav
Converted IY.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_U.wav.wav
26
Converted IY.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_A.wav.wav
Converted IY.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_OO.wav.wav
Converted IY.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/IY_to_E.wav.wav
Converted O.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_IY.wav.wav
Converted O.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_AE.wav.wav
Converted O.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_ER.wav.wav
Converted O.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_I.wav.wav
Converted O.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_UH.wav.wav
Converted O.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_AH.wav.wav
Converted O.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_OW.wav.wav
Converted O.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_U.wav.wav
Converted O.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_A.wav.wav
Converted O.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_OO.wav.wav
Converted O.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/O_to_E.wav.wav
Converted AE.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_IY.wav.wav
Converted AE.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_O.wav.wav
Converted AE.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_ER.wav.wav
Converted AE.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_I.wav.wav
Converted AE.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_UH.wav.wav
Converted AE.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_AH.wav.wav
Converted AE.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_OW.wav.wav
Converted AE.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_U.wav.wav
Converted AE.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_A.wav.wav
Converted AE.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_OO.wav.wav
27
Converted AE.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AE_to_E.wav.wav
Converted ER.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_IY.wav.wav
Converted ER.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_O.wav.wav
Converted ER.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_AE.wav.wav
Converted ER.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_I.wav.wav
Converted ER.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_UH.wav.wav
Converted ER.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_AH.wav.wav
Converted ER.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_OW.wav.wav
Converted ER.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_U.wav.wav
Converted ER.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_A.wav.wav
Converted ER.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_OO.wav.wav
Converted ER.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/ER_to_E.wav.wav
Converted I.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_IY.wav.wav
Converted I.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_O.wav.wav
Converted I.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_AE.wav.wav
Converted I.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_ER.wav.wav
Converted I.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_UH.wav.wav
Converted I.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_AH.wav.wav
Converted I.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_OW.wav.wav
Converted I.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_U.wav.wav
Converted I.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_A.wav.wav
Converted I.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_OO.wav.wav
Converted I.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/I_to_E.wav.wav
Converted UH.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_IY.wav.wav
28
Converted UH.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_O.wav.wav
Converted UH.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_AE.wav.wav
Converted UH.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_ER.wav.wav
Converted UH.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_I.wav.wav
Converted UH.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_AH.wav.wav
Converted UH.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_OW.wav.wav
Converted UH.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_U.wav.wav
Converted UH.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_A.wav.wav
Converted UH.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_OO.wav.wav
Converted UH.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/UH_to_E.wav.wav
Converted AH.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_IY.wav.wav
Converted AH.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_O.wav.wav
Converted AH.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_AE.wav.wav
Converted AH.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_ER.wav.wav
Converted AH.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_I.wav.wav
Converted AH.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_UH.wav.wav
Converted AH.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_OW.wav.wav
Converted AH.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_U.wav.wav
Converted AH.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_A.wav.wav
Converted AH.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_OO.wav.wav
Converted AH.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/AH_to_E.wav.wav
Converted OW.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_IY.wav.wav
Converted OW.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_O.wav.wav
Converted OW.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_AE.wav.wav
29
Converted OW.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_ER.wav.wav
Converted OW.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_I.wav.wav
Converted OW.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_UH.wav.wav
Converted OW.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_AH.wav.wav
Converted OW.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_U.wav.wav
Converted OW.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_A.wav.wav
Converted OW.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_OO.wav.wav
Converted OW.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OW_to_E.wav.wav
Converted U.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_IY.wav.wav
Converted U.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_O.wav.wav
Converted U.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_AE.wav.wav
Converted U.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_ER.wav.wav
Converted U.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_I.wav.wav
Converted U.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_UH.wav.wav
Converted U.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_AH.wav.wav
Converted U.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_OW.wav.wav
Converted U.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_A.wav.wav
Converted U.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_OO.wav.wav
Converted U.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/U_to_E.wav.wav
Converted A.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_IY.wav.wav
Converted A.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_O.wav.wav
Converted A.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_AE.wav.wav
Converted A.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_ER.wav.wav
Converted A.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_I.wav.wav
30
Converted A.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_UH.wav.wav
Converted A.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_AH.wav.wav
Converted A.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_OW.wav.wav
Converted A.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_U.wav.wav
Converted A.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_OO.wav.wav
Converted A.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/A_to_E.wav.wav
Converted OO.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_IY.wav.wav
Converted OO.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_O.wav.wav
Converted OO.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_AE.wav.wav
Converted OO.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_ER.wav.wav
Converted OO.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_I.wav.wav
Converted OO.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_UH.wav.wav
Converted OO.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_AH.wav.wav
Converted OO.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_OW.wav.wav
Converted OO.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_U.wav.wav
Converted OO.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_A.wav.wav
Converted OO.wav → E.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/OO_to_E.wav.wav
Converted E.wav → IY.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_IY.wav.wav
Converted E.wav → O.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_O.wav.wav
Converted E.wav → AE.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_AE.wav.wav
Converted E.wav → ER.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_ER.wav.wav
Converted E.wav → I.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_I.wav.wav
Converted E.wav → UH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_UH.wav.wav
Converted E.wav → AH.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_AH.wav.wav
31
Converted E.wav → OW.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_OW.wav.wav
Converted E.wav → U.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_U.wav.wav
Converted E.wav → A.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_A.wav.wav
Converted E.wav → OO.wav and saved to
/content/drive/MyDrive/sip_assign_2que_5/E_to_OO.wav.wav
All vowel transformations completed!
32