Breaking down large audio files for Whisper ASR
Whisper ASR (automatic speech recognition) has the fascinating ability to convert spoken language into written text. But what if you have an audio file greater than 25MB? This Answer is tailored to guide you through the process of dividing those large audio files into manageable chunks for smooth interaction with Whisper ASR, complete with practical demonstrations.
The need for breaking down audio files
Whisper ASR has limitations on the size of the audio file that can be processed in a single request. Large audio files can lead to longer processing times and may exceed the API's size limits, currently 25MB. By breaking down large audio files into smaller chunks, we can overcome these challenges and ensure smooth processing.
Tools for segmenting audio files
Several efficient libraries and tools can aid in the segmentation of audio files. Some well-known examples include:
PyDub: A simple and easy-to-use Python library for audio processing.
SoX: A command-line utility that can handle various audio file formats and operations.
PyDub
PyDub is a popular Python library for working with audio. Here's how you can use it to break down a large audio file into smaller chunks:
Install PyDub: You can install PyDub using pip:
pip install pydub
Import PyDub: Import the AudioSegment class from PyDub:
from pydub import AudioSegment
Load the audio file: Load the large audio file you want to break down:
audio = AudioSegment.from_mp3("large-audio-file.mp3")
Break down the audio file: Divide the audio file into chunks of a specific duration (e.g., 30 seconds):
chunk_length = 30 * 1000 # in millisecondschunks = [audio[i:i + chunk_length] for i in range(0, len(audio), chunk_length)]
Save the chunks: Save each chunk as a separate file:
from pydub import AudioSegment# Load the large audio fileaudio = AudioSegment.from_mp3("/assets/sample.mp3")print("Length of original audio is ",len(audio)/1000, " seconds")# Define the chunk length (e.g., 30 seconds)chunk_length = 30 * 1000 # in milliseconds# Break down the audio file into chunkschunks = [audio[i:i + chunk_length] for i in range(0, len(audio), chunk_length)]# Save each chunk as a separate filefor i, chunk in enumerate(chunks):chunk.export(f"chunk-{i}.mp3", format="mp3")print(f"Successfully split the audio file into {len(chunks)} chunks.")
SoX
SoX, standing for Sound eXchange, is a command-line tool tailored for audio file manipulation. Here's a method to employ it for segmenting an extensive audio file:
Install SoX
On Windows:
Download the SoX executable file from the official SoX website.
Run the installer and follow the on-screen instructions.
On macOS:
You can install SoX using Homebrew:
brew install sox
On Linux (Debian/Ubuntu):
You can install SoX using the following command:
sudo apt-get install sox
Use the split effect
Use the split effect in your command line to break down the audio file into chunks of a specific duration (e.g., 30 seconds):
sox large-audio-file.wav chunk.wav split n 30
Conclusion
Breaking down large audio files into smaller chunks is an essential step when working with Whisper ASR, especially when dealing with extensive audio data. By using tools like PyDub and SoX, you can efficiently manage large audio files, ensuring that they are processed smoothly by Whisper ASR. Whether you prefer working with Python code or command-line utilities, these methods provide flexible solutions for handling large audio files in your speech recognition projects.
