Merge pull request #1927 from srujana-16/Audio-Splitting

 Audio splitting script added - GSSOC'23

Author: avinashkranjan

Audio Splitting/README.md

@@ -0,0 +1,22 @@
+# Audio Splitting
+
+This Python script allows you to split large audio files into smaller segments based on silence, making them suitable for transcription or further analysis.
+
+## Setup instructions
+
+- Download the repository and `cd` to the the folder by running the caommand `cd Audio\ splitter`
+- Run the script with the following command `python audio_split.py input_audio_file`
+    - `input_audio_file` - Provide the path to the audio file you want to split.
+
+## Output
+
+The audio chunks will be saved in a new folder on your local system. Each audio chunk is approximately 10-15 seconds long which is best suitable for transcription. 
+
+## Author(s)
+
+Srujana
+
+## Disclaimers, if any
+
+Use this section to mention if any particular disclaimer is required
+

Audio Splitting/audio-split.py

@@ -0,0 +1,159 @@
+from pydub import AudioSegment
+from pydub.silence import split_on_silence
+import os
+import collections
+import contextlib
+import sys
+import wave
+import os
+import webrtcvad
+
+def read_wave(path):
+
+    with contextlib.closing(wave.open(path, 'rb')) as wf:
+        num_channels = wf.getnchannels()
+        assert num_channels == 1
+        sample_width = wf.getsampwidth()
+        assert sample_width == 2
+        sample_rate = wf.getframerate()
+        assert sample_rate in (8000, 16000, 32000, 48000)
+        pcm_data = wf.readframes(wf.getnframes())
+        return pcm_data, sample_rate
+
+
+def write_wave(path, audio, sample_rate):
+
+    with contextlib.closing(wave.open(path, 'wb')) as wf:
+        wf.setnchannels(1)
+        wf.setsampwidth(2)
+        wf.setframerate(sample_rate)
+        wf.writeframes(audio)
+        frames = wf.getnframes()
+        return frames / float(sample_rate)
+
+
+class Frame(object):
+
+    def __init__(self, bytes, timestamp, duration):
+        self.bytes = bytes
+        self.timestamp = timestamp
+        self.duration = duration
+
+
+def frame_generator(frame_duration_ms, audio, sample_rate):
+
+    n = int(sample_rate * (frame_duration_ms / 1000.0) * 2)
+    offset = 0
+    timestamp = 0.0
+    duration = (float(n) / sample_rate) / 2.0
+    while offset + n < len(audio):
+        yield Frame(audio[offset:offset + n], timestamp, duration)
+        timestamp += duration
+        offset += n
+
+
+def vad_collector(sample_rate, frame_duration_ms,
+                  padding_duration_ms, vad, frames):
+
+    num_padding_frames = int(padding_duration_ms / frame_duration_ms)
+    ring_buffer = collections.deque(maxlen=num_padding_frames)
+    triggered = False
+
+    voiced_frames = []
+    for frame in frames:
+        is_speech = vad.is_speech(frame.bytes, sample_rate)
+
+
+        if not triggered:
+            ring_buffer.append((frame, is_speech))
+            num_voiced = len([f for f, speech in ring_buffer if speech])
+
+            if num_voiced > 0.9 * ring_buffer.maxlen:
+                triggered = True
+
+
+                for f, s in ring_buffer:
+                    voiced_frames.append(f)
+                ring_buffer.clear()
+        else:
+
+            voiced_frames.append(frame)
+            ring_buffer.append((frame, is_speech))
+            num_unvoiced = len([f for f, speech in ring_buffer if not speech])
+
+            if num_unvoiced > 0.9 * ring_buffer.maxlen:
+
+                triggered = False
+                yield b''.join([f.bytes for f in voiced_frames])
+                ring_buffer.clear()
+                voiced_frames = []
+    if triggered:
+        pass
+
+    if voiced_frames:
+        yield b''.join([f.bytes for f in voiced_frames])
+
+path = "./frontend/speech-transcription-app/public/Original data"
+if not os.path.exists(path):
+        os.makedirs(path)
+        print("Output folder created")
+else:
+        print("Output folder already present")
+        sys.exit()
+
+def folder(path):
+    if not os.path.exists(path):
+        os.makedirs(path)
+        print("Output folder created")
+    else:
+        print("Output folder already present")
+
+path = "./frontend/speech-transcription-app/public/Original data"
+folder(path)
+path = "./main/save"
+folder(path)
+path = "./main/discard"
+folder(path)
+
+file_name= "./main/mod_1.wav"
+op_path= "./frontend/speech-transcription-app/public/Original data/audio_chunks"
+
+
+
+def main(file_name,op_path):
+
+    if os.path.isdir(op_path):
+        print("Output folder already present")
+    else:
+        os.mkdir(op_path)
+        print("Output folder created")  
+    
+    audio, sample_rate = read_wave(file_name)
+    vad = webrtcvad.Vad(2)
+    frames = frame_generator(30, audio, sample_rate)
+    segments = vad_collector(sample_rate, 30, 300, vad, frames)
+
+    for i, segment in enumerate(segments):
+        path = op_path+'/'+'chunk%004d.wav' % (i+1,)
+        print(' Writing %s' %(path,))
+        write_wave(path, segment, sample_rate )
+
+
+
+# sys.argv[1]
+
+# sys.argv[2]
+file_name= "./main/mod_1.wav"
+op_path= "./frontend/speech-transcription-app/public/Original data/audio_chunks"
+main(file_name,op_path)
+
+print("Audio Splitting Done")
+
+
+
+
+
+
+
+
+

SCRIPTS.md

@@ -103,4 +103,6 @@
 | 101\.     |Story Generator | This script randomly selects a character, setting, action, and conclusion from predefined lists and generates a story using these elements. | [Take Me](./Story_Generator/story_generator.py) | [Shraddha Singh](https://github.com/shraddha761)
 | 102\.     | Scientific Calculator | This python program will help to solve the hardest problems of trigonometry, exponents functions, logarithmic functions, etc. in very easy way. This program has a best User interface of the scientific calculator and provide a best user experience | [Take Me](./Scientific_Calculator) | [Avdhesh Varshney](https://github.com/Avdhesh-Varshney)
 | 103\.     | Chess Game | Chess Game is created using PYTHON script that provides user a interactive platform to play chess game. This program will create a interactive GUI of chess board for the user. Directly started in the terminal. | [Take Me](./Chess-Game/) | [Avdhesh Varshney](https:github.com/Avdhesh-Varshney)
+| 104\.     | Audio splitting script  | This Python script allows you to split large audio files into smaller segments based on silence, making them suitable for transcription or further analysis. | [Take Me](https://github.com/avinashkranjan/Amazing-Python-Scripts/tree/master/Audio\Splitting) |  [Srujana Vanka](https://github.com/srujana-16) |
+