Update README.md

simplifying the readme

README.md

@@ -11,67 +11,44 @@ language:
 - en
 pretty_name: Speaker Identification Toolkit
 ---
-# Speaker Identification Toolkit
-
-## Overview
-
-This toolkit provides a comprehensive suite of scripts for audio processing and speaker identification tasks. It includes features like video-to-audio conversion, speaker diarization, speaker isolation, and audio trimming.
-
-## Scripts
-
-### 1. Dataset Creation (Video to Audio Extraction)
-
-- **Functionality:** Extracts audio tracks from video files.
-- **Default Directories:**
-  - Input: `videos`
-  - Output: `wavs`
-- **Behavior:**
-  - Auto-creates `videos` and `wavs` directories in the script folder.
-  - Pauses execution to allow the user to populate the `videos` directory before processing.
-  - Processes all `.mkv` and `.mp4` files in the `videos` directory.
-  - Will create WAV's for use with model training: mono, pcm_s16le
-
-### 2. Speaker Diarization
-
-- **Functionality:** Processes audio files and generates speaker diarization metadata.
-- **Default Directories:**
-  - Input: `wavs`
-  - Output: `jsons`
-- **Behavior:**
-  - Auto-creates `wavs` and `jsons` directories in the script folder.
-  - Includes a prompt for the Hugging Face token with validation.
-  - Pauses execution to allow the user to populate the `wavs` directory.
-  - Generates diarization metadata in `.json` format for all `.wav` files in the `wavs` directory.
-
-### 3. Speaker Isolation and Trimming
-
-- **Functionality:** Isolates and trims audio segments based on speaker diarization metadata.
-- **Default Directories:**
-  - Input JSON: `jsons`
-  - Input WAV: `wavs`
-  - Output: `targeted`
-- **Behavior:**
-  - Auto-creates `jsons`, `wavs`, and `targeted` directories in the script folder.
-  - Pauses execution to allow the user to populate the `jsons` and `wavs` directories.
-  - Processes each `.json` file and its corresponding `.wav` file to extract and trim speaker-specific segments.
-  - Outputs trimmed audio clips in the `targeted` directory.
-
-## Common Features
-
-- All scripts auto-create necessary directories in the same folder as the script.
-- Scripts pause execution at key points to allow the user to populate input directories.
-- You can manually create the directories in advance and place media in it, for quicker processing.
-- Rich console output for enhanced user interaction and error handling.
-
-## Hugging Face Token
-
-- Required for the Speaker Diarization script.
-- Token validation is performed before processing.
-- Update your token in the script or provide it at runtime when prompted.
-
-## Notes
-
-- Ensure all input files are placed in the correct directories before running the scripts.
-- Output files will be saved in the corresponding output directories, which are automatically created if they do not exist.
-- When processing multi-speakers in multi-episode files, like a TV series spanning multiple seasons, it is best practice to listen to a few segments of the speaker before confirming.
-- If you make a mistake, stop the script and remove the bottom most line in your mappings CSV; the script will re-process it on next run.
+# Speaker Identification Toolkit (Speaker Diarization)
+
+This repository contains Python scripts for processing audio and video files, focusing on speaker diarization, speaker identification, audio extraction, and dataset creation. These tools leverage `ffmpeg`, `pyannote.audio`, and other Python libraries for efficient and accurate processing.
+
+## Workflow
+
+1. **Extract Audio from Videos**:
+   Use `dataset-creation.py` to extract English audio tracks from video files.
+
+2. **Generate Speaker Diarization Data**:
+   Use `diarize-dataset.py` to process the extracted WAV files and generate JSON files containing diarization data.
+
+3. **Identify Target Speaker**:
+   Use `identify-speaker.py` to play audio segments from diarization files and map the target speaker interactively.
+
+4. **Isolate and Trim Target Speaker Audio**:
+   Run `isolate-trim.py` to extract and trim the target speaker's audio segments for dataset creation.
+
+## Dependencies
+
+Ensure you have the following installed:
+
+- Python 3.8+
+
+- `ffmpeg`:
+  Install `ffmpeg` via your system's package manager or [official site](https://ffmpeg.org/).
+
+## Configuration
+
+The script will automatically create the folders it needs, pause for users to populate them with data, or proceed without prompt if they're already populated.
+
+- **Video Input Directory**: `base-folder/videos`
+- **WAV Output Directory**: `base-folder/wavs`
+- **JSON Output Directory**: `base-folder/jsons`
+- **Speaker Mapping File**: `base-folder/scripts/mappings.csv`
+- **Processed Speaker Output Directory**: `base-folder/targeted`
+
+**Additionally:**
+
+- For `diarize-dataset.py`, set the Hugging Face API token in the script manually for faster, prompt-free processing. Insert it between the final set of quotes on line 29.
+