Minor README changes

Author: abhirooptalasila

README.md

@@ -14,6 +14,7 @@
 
 AutoSub is a CLI application to generate subtitle file (.srt) for any video file using [Mozilla DeepSpeech](https://github.com/mozilla/DeepSpeech). I use the DeepSpeech Python API to run inference on audio segments and [pyAudioAnalysis](https://github.com/tyiannak/pyAudioAnalysis) to split the initial audio on silent segments, producing multiple small files.
 
+
 ## Motivation
 
 In the age of OTT platforms, there are still some who prefer to download movies/videos from YouTube/Facebook or even torrents rather than stream. I am one of them and on one such occasion, I couldn't find the subtitle file for a particular movie I had downloaded. Then the idea for AutoSub struck me and since I had worked with DeepSpeech previously, I decided to use it. 
@@ -43,6 +44,12 @@ In the age of OTT platforms, there are still some who prefer to download movies/
     ```bash
     $ mkdir audio output
     ```
+* Install FFMPEG. If you're running Ubuntu, this should work fine.
+    ```bash
+    $ sudo apt-get install ffmpeg
+    $ ffmpeg -version               # I'm running 4.1.4
+    ```
+
 
 ## How-to example
 
@@ -52,19 +59,30 @@ In the age of OTT platforms, there are still some who prefer to download movies/
     ```
 * After the script finishes, the SRT file is saved in `output/`
 * Open the video file and add this SRT file as a subtitle, or you can just drag and drop in VLC.
-* When I tested the script on my laptop, it took about 40 minutes to generate the SRT file for a 70 minutes video file. 
+
 
 ## How it works
 
+Mozilla DeepSpeech is an amazing open-source speech-to-text engine with support for fine-tuning using custom datasets, external language models, exporting memory-mapped models and a lot more. You should definitely check it out for STT tasks. So, when you first run the script, I use FFMPEG to **extract the audio** from the video and save it in `audio/`. By default DeepSpeech is configured to accept 16kHz audio samples for inference, hence while extracting I make FFMPEG use 16kHz sampling rate. 
+
+Then, I use [pyAudioAnalysis](https://github.com/tyiannak/pyAudioAnalysis) for silence removal - which basically takes the large audio file initially extracted, and splits it wherever silent regions are encountered, resulting in smaller audio segments which are much easier to process. I haven't used the whole library, instead I've integrated parts of it in `autosub/featureExtraction.py` and `autosub/trainAudio.py` All these audio files are stored in `audio/`. Then for each audio segment, I perform DeepSpeech inference on it, and write the inferred text in a SRT file. After all files are processed, the final SRT file is stored in `output/`.
+
+When I tested the script on my laptop, it took about **40 minutes to generate the SRT file for a 70 minutes video file**. My config is an i5 dual-core @ 2.5 Ghz and 8 gigs of RAM. Ideally, the whole process shouldn't take more than 60% of the duration of original video file. 
+
 
 ## TO-DO
 
+* Pre-process inferred text before writing to file (prettify)
+* Add progress bar to extract_audio()
+* GUI support (?)
+
 
 ## Contributing
 
+I would love to follow up on any suggestions/issues you find :)
+
 
 ## References
 1. https://github.com/mozilla/DeepSpeech/
 2. https://github.com/tyiannak/pyAudioAnalysis
-3. https://deepspeech.readthedocs.io/
-4. 
+3. https://deepspeech.readthedocs.io/