├── LICENSE ├── Listen-Audio └── listenaudio.py ├── Manipulate-Framerate_Channel_Samplewidth └── conversionrate.py ├── Merge-Audio └── mergeaudio.py ├── Plot-AudioSignal ├── Figure_1.png └── plotaudio.py ├── README.MD ├── Silence-Remove ├── README.MD ├── example.py ├── requirements.txt └── silenceremove.py ├── Speed-Change └── speedchange.py └── Split-Audio └── splitaudio.py /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /Listen-Audio/listenaudio.py: -------------------------------------------------------------------------------- 1 | # Import packages 2 | from pydub import AudioSegment 3 | from pydub.playback import play 4 | 5 | 6 | # Play audio 7 | playaudio = AudioSegment.from_file("bala.wav", format="wav") 8 | play(playaudio) -------------------------------------------------------------------------------- /Manipulate-Framerate_Channel_Samplewidth/conversionrate.py: -------------------------------------------------------------------------------- 1 | from pydub import AudioSegment 2 | sound = AudioSegment.from_file("chunk.wav") 3 | 4 | print("----------Before Conversion--------") 5 | print("Frame Rate", sound.frame_rate) 6 | print("Channel", sound.channels) 7 | print("Sample Width",sound.sample_width) 8 | 9 | # Change Frame Rate 10 | sound = sound.set_frame_rate(16000) 11 | 12 | # Change Channel 13 | sound = sound.set_channels(1) 14 | 15 | # Change Sample Width 16 | sound = sound.set_sample_width(2) 17 | 18 | # Export the Audio to get the changed content 19 | sound.export("convertedrate.wav", format ="wav") -------------------------------------------------------------------------------- /Merge-Audio/mergeaudio.py: -------------------------------------------------------------------------------- 1 | import os 2 | from pydub import AudioSegment 3 | import glob 4 | 5 | # if "audio" folder not exists, it will create 6 | if not os.path.isdir("audio"): 7 | os.mkdir("audio") 8 | 9 | # Grab the Audio files in "audio" folder 10 | wavfiles = glob.glob("./audio/*.wav") 11 | print(wavfiles) 12 | 13 | # Loopting each file and include in Audio Segment 14 | wavs = [AudioSegment.from_wav(wav) for wav in wavfiles] 15 | 16 | combined = wavs[0] 17 | 18 | # Appending all the audio file 19 | for wav in wavs[1:]: 20 | combined = combined.append(wav) 21 | 22 | # Export Merged Audio File 23 | combined.export("Mergedaudio.wav", format="wav") -------------------------------------------------------------------------------- /Plot-AudioSignal/Figure_1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ngbala6/Audio-Processing/dea3690d1fd093170506ac176a09c792dcb2a23b/Plot-AudioSignal/Figure_1.png -------------------------------------------------------------------------------- /Plot-AudioSignal/plotaudio.py: -------------------------------------------------------------------------------- 1 | # Loading the Libraries 2 | from scipy.io.wavfile import read 3 | import numpy as np 4 | import matplotlib.pyplot as plt 5 | 6 | # Read the Audiofile 7 | samplerate, data = read('6TU5302374.wav') 8 | # Frame rate for the Audio 9 | print(samplerate) 10 | 11 | # Duration of the audio in Seconds 12 | duration = len(data)/samplerate 13 | print("Duration of Audio in Seconds", duration) 14 | print("Duration of Audio in Minutes", duration/60) 15 | 16 | time = np.arange(0,duration,1/samplerate) 17 | 18 | # Plotting the Graph using Matplotlib 19 | plt.plot(time,data) 20 | plt.xlabel('Time [s]') 21 | plt.ylabel('Amplitude') 22 | plt.title('6TU5302374.wav') 23 | plt.show() -------------------------------------------------------------------------------- /README.MD: -------------------------------------------------------------------------------- 1 | # Audio Processing and Remove Silence using Python 2 | Audio Processing Techniques like Play an Audio, Plot the Audio Signals, Merge and Split Audio, Change the Frame Rate, 3 | Sample Width and Channel, Silence Remove in Audio, Slow down and Speed up audio 4 | 5 | This Repository includes how to 6 | * Play an audio 7 | * Plot the Audio Signals 8 | * Merge and Split Audio Contents 9 | * Slow down and Speed up the Audio - Speed Changer 10 | * Change the Frame Rate, Channels and Sample Width 11 | * Silence Remove 12 | 13 | # Installation 14 | ``` 15 | pip install webrtcvad==2.0.10 wave pydub simpleaudio numpy matplotlib 16 | ``` 17 | -------------------------------------------------------------------------------- /Silence-Remove/README.MD: -------------------------------------------------------------------------------- 1 | Hello Welcome, here you can remove your silence from audio files 2 | 3 | # Step 1: 4 | 5 | Install the Requirements by using "pip install -r requirements.txt" 6 | 7 | # Step 2: 8 | 9 | Run the "Silence-Remove.py 'aggressiveness' " python file. You will get non-silenced audio as "Non-Silenced-Audio.wav". 10 | 11 | Set the aggressiveness mode, which is an integer between 0 and 3. 0 is the least aggressive about filtering out non-speech, 3 is the most aggressive. 12 | 13 | For Example : "Silence-Remove.py 3 abc.wav" 14 | -------------------------------------------------------------------------------- /Silence-Remove/example.py: -------------------------------------------------------------------------------- 1 | import collections 2 | import contextlib 3 | import sys 4 | import wave 5 | import webrtcvad 6 | 7 | 8 | def read_wave(path): 9 | """Reads a .wav file. 10 | 11 | Takes the path, and returns (PCM audio data, sample rate). 12 | """ 13 | with contextlib.closing(wave.open(path, 'rb')) as wf: 14 | num_channels = wf.getnchannels() 15 | assert num_channels == 1 16 | sample_width = wf.getsampwidth() 17 | assert sample_width == 2 18 | sample_rate = wf.getframerate() 19 | assert sample_rate in (8000, 16000, 32000, 48000) 20 | pcm_data = wf.readframes(wf.getnframes()) 21 | return pcm_data, sample_rate 22 | 23 | 24 | def write_wave(path, audio, sample_rate): 25 | """Writes a .wav file. 26 | 27 | Takes path, PCM audio data, and sample rate. 28 | """ 29 | with contextlib.closing(wave.open(path, 'wb')) as wf: 30 | wf.setnchannels(1) 31 | wf.setsampwidth(2) 32 | wf.setframerate(sample_rate) 33 | wf.writeframes(audio) 34 | 35 | 36 | class Frame(object): 37 | """Represents a "frame" of audio data.""" 38 | def __init__(self, bytes, timestamp, duration): 39 | self.bytes = bytes 40 | self.timestamp = timestamp 41 | self.duration = duration 42 | 43 | 44 | def frame_generator(frame_duration_ms, audio, sample_rate): 45 | """Generates audio frames from PCM audio data. 46 | 47 | Takes the desired frame duration in milliseconds, the PCM data, and 48 | the sample rate. 49 | 50 | Yields Frames of the requested duration. 51 | """ 52 | n = int(sample_rate * (frame_duration_ms / 1000.0) * 2) 53 | offset = 0 54 | timestamp = 0.0 55 | duration = (float(n) / sample_rate) / 2.0 56 | while offset + n < len(audio): 57 | yield Frame(audio[offset:offset + n], timestamp, duration) 58 | timestamp += duration 59 | offset += n 60 | 61 | 62 | def vad_collector(sample_rate, frame_duration_ms, 63 | padding_duration_ms, vad, frames): 64 | """Filters out non-voiced audio frames. 65 | 66 | Given a webrtcvad.Vad and a source of audio frames, yields only 67 | the voiced audio. 68 | 69 | Uses a padded, sliding window algorithm over the audio frames. 70 | When more than 90% of the frames in the window are voiced (as 71 | reported by the VAD), the collector triggers and begins yielding 72 | audio frames. Then the collector waits until 90% of the frames in 73 | the window are unvoiced to detrigger. 74 | 75 | The window is padded at the front and back to provide a small 76 | amount of silence or the beginnings/endings of speech around the 77 | voiced frames. 78 | 79 | Arguments: 80 | 81 | sample_rate - The audio sample rate, in Hz. 82 | frame_duration_ms - The frame duration in milliseconds. 83 | padding_duration_ms - The amount to pad the window, in milliseconds. 84 | vad - An instance of webrtcvad.Vad. 85 | frames - a source of audio frames (sequence or generator). 86 | 87 | Returns: A generator that yields PCM audio data. 88 | """ 89 | num_padding_frames = int(padding_duration_ms / frame_duration_ms) 90 | # We use a deque for our sliding window/ring buffer. 91 | ring_buffer = collections.deque(maxlen=num_padding_frames) 92 | # We have two states: TRIGGERED and NOTTRIGGERED. We start in the 93 | # NOTTRIGGERED state. 94 | triggered = False 95 | 96 | voiced_frames = [] 97 | for frame in frames: 98 | is_speech = vad.is_speech(frame.bytes, sample_rate) 99 | 100 | sys.stdout.write('1' if is_speech else '0') 101 | if not triggered: 102 | ring_buffer.append((frame, is_speech)) 103 | num_voiced = len([f for f, speech in ring_buffer if speech]) 104 | # If we're NOTTRIGGERED and more than 90% of the frames in 105 | # the ring buffer are voiced frames, then enter the 106 | # TRIGGERED state. 107 | if num_voiced > 0.9 * ring_buffer.maxlen: 108 | triggered = True 109 | sys.stdout.write('+(%s)' % (ring_buffer[0][0].timestamp,)) 110 | # We want to yield all the audio we see from now until 111 | # we are NOTTRIGGERED, but we have to start with the 112 | # audio that's already in the ring buffer. 113 | for f, s in ring_buffer: 114 | voiced_frames.append(f) 115 | ring_buffer.clear() 116 | else: 117 | # We're in the TRIGGERED state, so collect the audio data 118 | # and add it to the ring buffer. 119 | voiced_frames.append(frame) 120 | ring_buffer.append((frame, is_speech)) 121 | num_unvoiced = len([f for f, speech in ring_buffer if not speech]) 122 | # If more than 90% of the frames in the ring buffer are 123 | # unvoiced, then enter NOTTRIGGERED and yield whatever 124 | # audio we've collected. 125 | if num_unvoiced > 0.9 * ring_buffer.maxlen: 126 | sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration)) 127 | triggered = False 128 | yield b''.join([f.bytes for f in voiced_frames]) 129 | ring_buffer.clear() 130 | voiced_frames = [] 131 | if triggered: 132 | sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration)) 133 | sys.stdout.write('\n') 134 | # If we have any leftover voiced audio when we run out of input, 135 | # yield it. 136 | if voiced_frames: 137 | yield b''.join([f.bytes for f in voiced_frames]) 138 | 139 | 140 | def main(args): 141 | if len(args) != 2: 142 | sys.stderr.write( 143 | 'Usage: example.py \n') 144 | sys.exit(1) 145 | audio, sample_rate = read_wave(args[1]) 146 | vad = webrtcvad.Vad(int(args[0])) 147 | frames = frame_generator(30, audio, sample_rate) 148 | frames = list(frames) 149 | segments = vad_collector(sample_rate, 30, 300, vad, frames) 150 | for i, segment in enumerate(segments): 151 | path = 'chunk-%002d.wav' % (i,) 152 | print(' Writing %s' % (path,)) 153 | write_wave(path, segment, sample_rate) 154 | 155 | 156 | if __name__ == '__main__': 157 | main(sys.argv[1:]) 158 | -------------------------------------------------------------------------------- /Silence-Remove/requirements.txt: -------------------------------------------------------------------------------- 1 | webrtcvad==2.0.10 2 | wave 3 | -------------------------------------------------------------------------------- /Silence-Remove/silenceremove.py: -------------------------------------------------------------------------------- 1 | import collections 2 | import contextlib 3 | import sys 4 | import wave 5 | import webrtcvad 6 | 7 | 8 | def read_wave(path): 9 | """Reads a .wav file. 10 | Takes the path, and returns (PCM audio data, sample rate). 11 | """ 12 | with contextlib.closing(wave.open(path, 'rb')) as wf: 13 | num_channels = wf.getnchannels() 14 | assert num_channels == 1 15 | sample_width = wf.getsampwidth() 16 | assert sample_width == 2 17 | sample_rate = wf.getframerate() 18 | assert sample_rate in (8000, 16000, 32000, 48000) 19 | pcm_data = wf.readframes(wf.getnframes()) 20 | return pcm_data, sample_rate 21 | 22 | 23 | def write_wave(path, audio, sample_rate): 24 | """Writes a .wav file. 25 | Takes path, PCM audio data, and sample rate. 26 | """ 27 | with contextlib.closing(wave.open(path, 'wb')) as wf: 28 | wf.setnchannels(1) 29 | wf.setsampwidth(2) 30 | wf.setframerate(sample_rate) 31 | wf.writeframes(audio) 32 | 33 | 34 | class Frame(object): 35 | """Represents a "frame" of audio data.""" 36 | def __init__(self, bytes, timestamp, duration): 37 | self.bytes = bytes 38 | self.timestamp = timestamp 39 | self.duration = duration 40 | 41 | 42 | def frame_generator(frame_duration_ms, audio, sample_rate): 43 | """Generates audio frames from PCM audio data. 44 | Takes the desired frame duration in milliseconds, the PCM data, and 45 | the sample rate. 46 | Yields Frames of the requested duration. 47 | """ 48 | n = int(sample_rate * (frame_duration_ms / 1000.0) * 2) 49 | offset = 0 50 | timestamp = 0.0 51 | duration = (float(n) / sample_rate) / 2.0 52 | while offset + n < len(audio): 53 | yield Frame(audio[offset:offset + n], timestamp, duration) 54 | timestamp += duration 55 | offset += n 56 | 57 | 58 | def vad_collector(sample_rate, frame_duration_ms, 59 | padding_duration_ms, vad, frames): 60 | """Filters out non-voiced audio frames. 61 | Given a webrtcvad.Vad and a source of audio frames, yields only 62 | the voiced audio. 63 | Uses a padded, sliding window algorithm over the audio frames. 64 | When more than 90% of the frames in the window are voiced (as 65 | reported by the VAD), the collector triggers and begins yielding 66 | audio frames. Then the collector waits until 90% of the frames in 67 | the window are unvoiced to detrigger. 68 | The window is padded at the front and back to provide a small 69 | amount of silence or the beginnings/endings of speech around the 70 | voiced frames. 71 | Arguments: 72 | sample_rate - The audio sample rate, in Hz. 73 | frame_duration_ms - The frame duration in milliseconds. 74 | padding_duration_ms - The amount to pad the window, in milliseconds. 75 | vad - An instance of webrtcvad.Vad. 76 | frames - a source of audio frames (sequence or generator). 77 | Returns: A generator that yields PCM audio data. 78 | """ 79 | num_padding_frames = int(padding_duration_ms / frame_duration_ms) 80 | # We use a deque for our sliding window/ring buffer. 81 | ring_buffer = collections.deque(maxlen=num_padding_frames) 82 | # We have two states: TRIGGERED and NOTTRIGGERED. We start in the 83 | # NOTTRIGGERED state. 84 | triggered = False 85 | 86 | voiced_frames = [] 87 | for frame in frames: 88 | is_speech = vad.is_speech(frame.bytes, sample_rate) 89 | 90 | sys.stdout.write('1' if is_speech else '0') 91 | if not triggered: 92 | ring_buffer.append((frame, is_speech)) 93 | num_voiced = len([f for f, speech in ring_buffer if speech]) 94 | # If we're NOTTRIGGERED and more than 90% of the frames in 95 | # the ring buffer are voiced frames, then enter the 96 | # TRIGGERED state. 97 | if num_voiced > 0.9 * ring_buffer.maxlen: 98 | triggered = True 99 | sys.stdout.write('+(%s)' % (ring_buffer[0][0].timestamp,)) 100 | # We want to yield all the audio we see from now until 101 | # we are NOTTRIGGERED, but we have to start with the 102 | # audio that's already in the ring buffer. 103 | for f, s in ring_buffer: 104 | voiced_frames.append(f) 105 | ring_buffer.clear() 106 | else: 107 | # We're in the TRIGGERED state, so collect the audio data 108 | # and add it to the ring buffer. 109 | voiced_frames.append(frame) 110 | ring_buffer.append((frame, is_speech)) 111 | num_unvoiced = len([f for f, speech in ring_buffer if not speech]) 112 | # If more than 90% of the frames in the ring buffer are 113 | # unvoiced, then enter NOTTRIGGERED and yield whatever 114 | # audio we've collected. 115 | if num_unvoiced > 0.9 * ring_buffer.maxlen: 116 | sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration)) 117 | triggered = False 118 | yield b''.join([f.bytes for f in voiced_frames]) 119 | ring_buffer.clear() 120 | voiced_frames = [] 121 | if triggered: 122 | sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration)) 123 | sys.stdout.write('\n') 124 | # If we have any leftover voiced audio when we run out of input, 125 | # yield it. 126 | if voiced_frames: 127 | yield b''.join([f.bytes for f in voiced_frames]) 128 | 129 | 130 | def main(args): 131 | if len(args) != 2: 132 | sys.stderr.write( 133 | 'Usage: Silence-Remove.py \n') 134 | sys.exit(1) 135 | audio, sample_rate = read_wave(args[1]) 136 | vad = webrtcvad.Vad(int(args[0])) 137 | frames = frame_generator(30, audio, sample_rate) 138 | frames = list(frames) 139 | segments = vad_collector(sample_rate, 30, 300, vad, frames) 140 | 141 | # Segmenting the Voice audio and save it in list as bytes 142 | concataudio = [segment for segment in segments] 143 | 144 | joinedaudio = b"".join(concataudio) 145 | 146 | write_wave("Non-Silenced-Audio.wav", joinedaudio, sample_rate) 147 | 148 | 149 | if __name__ == '__main__': 150 | main(sys.argv[1:]) -------------------------------------------------------------------------------- /Speed-Change/speedchange.py: -------------------------------------------------------------------------------- 1 | from pydub import AudioSegment 2 | 3 | sound = AudioSegment.from_file("chunk.wav") 4 | 5 | def speed_change(sound, speed): 6 | 7 | sound_with_altered_frame_rate = sound._spawn(sound.raw_data, overrides={ 8 | "frame_rate": int(sound.frame_rate * speed) 9 | }) 10 | 11 | filename = 'chunk1.wav' 12 | 13 | sound_with_altered_frame_rate.export(filename, format ="wav") 14 | 15 | # To Slow down audio 16 | slow_sound = speed_change(sound, 0.8) 17 | # To Speed up the audio 18 | #fast_sound = speed_change(sound, 1.2) 19 | 20 | # 1.0 is the Normal Speed Rate -------------------------------------------------------------------------------- /Split-Audio/splitaudio.py: -------------------------------------------------------------------------------- 1 | from pydub import AudioSegment 2 | import os 3 | 4 | if not os.path.isdir("splitaudio"): 5 | os.mkdir("splitaudio") 6 | 7 | audio = AudioSegment.from_file("02072018-083922_OUT_TATA_232_012156853818.gsm") 8 | lengthaudio = len(audio) 9 | print("Length of Audio File", lengthaudio) 10 | 11 | start = 0 12 | # In Milliseconds, this will cut 10 Sec of audio 13 | threshold = 10000 14 | end = 0 15 | counter = 0 16 | 17 | while start < len(audio): 18 | 19 | end += threshold 20 | 21 | print(start , end) 22 | 23 | chunk = audio[start:end] 24 | 25 | filename = f'bala/chunk{counter}.wav' 26 | 27 | chunk.export(filename, format="wav") 28 | 29 | counter +=1 30 | 31 | start += threshold 32 | 33 | 34 | 35 | 36 | 37 | --------------------------------------------------------------------------------