How to Transcribe Audio to text (Google Colab Version)👇

Step 1: Clone the Fairseq Git Repo

import os

!git clone https://github.com/pytorch/fairseq

# Get the current working directory
current_dir = os.getcwd()

# Create the directory paths
audio_samples_dir = os.path.join(current_dir, "audio_samples")
temp_dir = os.path.join(current_dir, "temp_dir")

# Create the directories if they don't exist
os.makedirs(audio_samples_dir, exist_ok=True)
os.makedirs(temp_dir, exist_ok=True)


# Change current working directory
os.chdir('fairseq')

!pwd

Step 2: Install requirements and build

Be patient, takes some minutes

!pip install --editable ./

Step 3: Install Tensor Board

!pip install tensorboardX

Step 4: Download your preferred model

Un comment to download any

# # MMS-1B:FL102 model - 102 Languages - FLEURS Dataset
# !wget -P ./models_new 'https://dl.fbaipublicfiles.com/mms/asr/mms1b_fl102.pt'

# # MMS-1B:L1107 - 1107 Languages - MMS-lab Dataset
# !wget -P ./models_new 'https://dl.fbaipublicfiles.com/mms/asr/mms1b_l1107.pt'

# MMS-1B-all - 1162 Languages - MMS-lab + FLEURS + CV + VP + MLS
!wget -P ./models_new 'https://dl.fbaipublicfiles.com/mms/asr/mms1b_all.pt'

Step 5: Upload your audio(s)

Create a folder on path '/content/audio_samples/' and upload your .wav audio files that you need to transcribe e.g. '/content/audio_samples/small_trim4.wav' Note: You need to make sure that the audio data you are using has a sample rate of 16000 You can easily do this with FFMPEG like the example below that converts .mp3 file to .wav and fixing the audio sample rate

ffmpeg -i .\small_trim4.mp3 -ar 16000 .\wav_formats\small_trim4.wav

Step 6: Run Inference and transcribe your audio(s)

Takes some time for long audios

import os

os.environ["TMPDIR"] = '/content/temp_dir'
os.environ["PYTHONPATH"] = "."
os.environ["PREFIX"] = "INFER"
os.environ["HYDRA_FULL_ERROR"] = "1"
os.environ["USER"] = "micro"

!python examples/mms/asr/infer/mms_infer.py --model "/content/fairseq/models_new/mms1b_all.pt" --lang "swh" --audio "/content/audio_samples/small_trim4.wav"

After this you'll get your preffered transcription I have this Collab Example in my GitHub Repo👉 fairseq_meta_mms_Google_Colab_implementation