Update README.md

README.md

@@ -61,3 +61,75 @@ configs:
   - split: test.other
     path: data/test.other-*
 ---
+
+# Condensed LibriSpeech ASR
+
+This dataset is a condensed version of the [LibriSpeech ASR dataset](https://huggingface.co/datasets/openslr/librispeech_asr), created by subsampling approximately 10% of the original data from each split. It is intended for quick experimentation, prototyping, and debugging when working with Automatic Speech Recognition (ASR) tasks.
+
+## Dataset Details
+
+- **Original Dataset:** [LibriSpeech ASR](https://huggingface.co/datasets/openslr/librispeech_asr)
+- **Condensation Ratio:** Approximately 10% of the full dataset
+- **Splits Included:**
+  - `train.clean.100`
+  - `train.clean.360`
+  - `train.other.500`
+  - `validation.clean`
+  - `validation.other`
+  - `test.clean`
+  - `test.other`
+
+For each split, a default number of examples was extracted:
+- **Training Splits:** 1,000 examples each
+- **Validation/Test Splits:** 100 examples each
+
+## Data Format
+
+Each sample in the dataset contains the following fields:
+
+- **file:**  
+  A path to the original audio file (FLAC format).
+
+- **audio:**  
+  A dictionary containing:
+  - `path`: Path to the audio file.
+  - `array`: The decoded audio waveform as a NumPy array.
+  - `sampling_rate`: The sampling rate (typically 16 kHz).
+
+- **text:**  
+  The transcription corresponding to the audio.
+
+- **id:**  
+  A unique identifier for the sample.
+
+- **speaker_id:**  
+  A unique identifier for the speaker.
+
+- **chapter_id:**  
+  An identifier corresponding to the audiobook chapter.
+
+## How Was This Dataset Created?
+
+The condensed dataset was generated by streaming the full [LibriSpeech ASR dataset](https://huggingface.co/datasets/openslr/librispeech_asr) using the Hugging Face Datasets library and selecting approximately 10% of each split. This process preserves the original structure and fields, enabling seamless use with models and workflows designed for LibriSpeech.
+
+## Usage Example
+
+Below is a Python snippet to load and inspect the dataset:
+
+```python
+from datasets import load_dataset
+
+# Load the condensed dataset from the Hugging Face Hub
+dataset = load_dataset("nyalpatel/condensed_librispeech_asr")
+
+# Access a specific split (e.g., test.clean)
+test_dataset = dataset["test.clean"]
+
+# Display the first example in the test set
+print(test_dataset[0])
+
+
+
+
+
+