Update column names for YTSeg (Titles) config + update README

README.md

@@ -152,15 +152,36 @@ Multiple target formats are provided for different modeling approaches.
 | Testing    | 1,448 (7.5%)   |
 | Total      | 19,299        |
 
+### <span style="font-variant:small-caps;">YTSeg</span> (Audio)
+
+The audio config provides the complete dataset with embedded audio files. Each video is represented with the same fields as the text config, plus an `audio` field containing the preprocessed audio data.
+
+#### Audio
+
+| Field  | Description |
+|--------|-------------|
+| `audio` | Audio data preprocessed into .mp3 format with a standardized sample rate of 16,000 Hz and a single channel (mono). |
+
+All other fields (transcripts, target representations, and metadata) are identical to the Text config described above.
+
+#### Partition Statistics
+
+| Partition  | # Examples    | Size (GB) |
+|------------|--------------|-----------|
+| Training   | 16,404 (85%)   | ~57.9 GB |
+| Validation | 1,447 (7.5%)   | ~5.1 GB |
+| Testing    | 1,448 (7.5%)   | ~5.3 GB |
+| Total      | 19,299        | ~68.3 GB |
+
 ### <span style="font-variant:small-caps;">YTSeg</span> (Titles)
 
 Each chapter of a video is represented as a JSON object with the following fields:
 
 | Field  | Description                                    |
 |--------------|------------------------------------------------|
-| `input`       | The complete chapter/section text.           |
-| `input_with_chapters`    | The complete chapter/section text with previous section titles prepended. |  
-| `target`     | The target chapter title.           |
+| `text_section_ref`       | The complete chapter/section text.           |
+| `text_section_prev_titles_ref`    | The complete chapter/section text with previous section titles prepended. |
+| `target_title`     | The target chapter title.           |
 | `channel_id` | The YouTube channel ID which this chapter's video belongs to.          |
 | `video_id`   | The YouTube video ID which this chapter belongs to.            |
 | `chapter_idx` | The index and placement of the chapter in the video (e.g., the first chapter has index `0`).  |
@@ -172,10 +193,6 @@ Each chapter of a video is represented as a JSON object with the following field
 | Testing    | 13,082 (7.6%)  |
 | Total      | 173,195       |
 
-### Audio Data
-
-We provide audio files for all examples in the dataset, preprocessed into the .mp3 format with a standardized sample rate of 16,000 Hz and a single channel (mono). These files are organized within the directory structure as follows: `data/audio/<channel_id>/<video_id>.mp3`.
-
 ### Video Data
 
 A download script for the video and audio data is provided.
@@ -186,20 +203,27 @@ python download_videos.py
 
 In the script, you can further specify a target folder (default is `./video`) and target formats in a priority list. 
 
-## Loading Text Data
+## Loading Data
 
-This repository comes with a simple, exemplary script to read in the text data with `pandas`.
+The dataset can be loaded directly using the HuggingFace `datasets` library:
 
 ```py
-from load_data import get_partition
-test_data = get_partition('test')
+from datasets import load_dataset
+
+# Load the audio config (with embedded audio)
+dataset = load_dataset("retkowski/ytseg", "audio", split="test")
+
+# Load the text config (text-only)
+dataset = load_dataset("retkowski/ytseg", "text", split="test")
+
+# Load the titles config
+dataset = load_dataset("retkowski/ytseg", "titles", split="test")
 ```
 
-Equivalently, to read in <span style="font-variant:small-caps;">YTSeg[Titles]</span>:
+**Note on Binary Labels:** The binary segmentation labels (e.g., `target_binary_ref`) are prefixed with `|=` to force the field to be stored as a string, preventing leading zeros from being lost during processing. For actual usage, strip the `|=` prefix:
 
 ```py
-from load_data import get_title_partition
-test_data = get_title_partition('test')
+binary_labels = dataset['target_binary_ref'].lstrip('|=')
 ```
 
 ## Citing
@@ -223,7 +247,11 @@ We kindly request you to cite our corresponding EACL 2024 paper if you use our d
 ```
 ## Changelog
 
-- 20.01.2025 -- Major data update: Added ASR transcripts, structured transcript targets with timestamps, and metadata for finer-grained analysis
+- 20.01.2025 -- Major data and format update:
+  - Added ASR transcripts (Whisper-tiny and Whisper-large), structured transcript targets with timestamps, and metadata for finer-grained analysis (speaker category, dominant speaker proportion, number of speakers, duration)
+  - Added audio config with HuggingFace Audio feature for seamless loading with embedded audio
+  - Updated to use HuggingFace `datasets` library for data loading (replacing local pandas scripts and use proper HF configs)
+  - Updated `YTSeg[Titles]` field names for clarity
 - 25.07.2024 -- Added complete list of chapter titles to `YTSeg` (`YTSeg[Titles]` is a filtered subset)
 - 09.04.2024 -- Added audio data
 - 27.02.2024 -- Initial release

data/partitions/yt_seg_titles.test.json

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