README.md first commit

Adding descriptions to the dataset.

README.md

@@ -1,3 +1,143 @@
 ---
 license: apache-2.0
+
+dataset_info:
+  features:
+  - name: session_id
+    dtype: string
+  - name: start_time
+    dtype: float
+  - name: end_time
+    dtype: float
+  - name: words
+    dtype: string
+  - name: speaker
+    dtype: string
+  splits:
+  - name: dev
+    num_bytes: 
+    num_examples: 142
+  - name: eval
+    num_bytes:
+    num_examples: 104
+  download_size: 
+  dataset_size:
 ---
+
+
+# Dataset Name: Dataset for ASR Speaker-Tagging Corrections (Speaker Diarization)
+
+
+## Description
+
+- This dataset is pairs of erroneous ASR output and speaker tagging, which are generated from a ASR system and speaker diarization system.
+Each source erroneous transcription is paired with human-annotated transcription, which has correct transcription and speaker tagging.
+- [SEGment-wise Long-form Speech Transcription annotation](#segment-wise-long-form-speech-transcription-annotation-seglst) (`SegLST`), the file format used in the [CHiME challenges](https://www.chimechallenge.org)
+
+
+Example) `session_ge1nse2c.seglst.json`
+
+```
+[
+...
+    {
+        "session_id": "session_ge1nse2c",
+        "words": "well that is the problem we have erroneous transcript and speaker tagging we want to correct it using large language models",
+        "start_time": 181.88,
+        "end_time": 193.3,
+        "speaker": "speaker1"
+    },
+    {
+        "session_id": "session_ge1nse2c",
+        "words": "it seems like a really interesting problem I feel that we can start with very simple methods",
+        "start_time": 194.48,
+        "end_time": 205.03,
+        "speaker": "speaker2"
+    },
+...
+]
+```
+
+## Structure
+
+### Data Split
+
+The dataset is divided into training and test splits:
+
+- Development Data: 142 entries
+  - 2 to 4 speakers in each session 
+  - Approximately 10 ~ 40 mins of recordings 
+- Evaluation Data: 104 entries
+  - 2 to 4 speakers in each session 
+  - Approximately 10 ~ 40 mins of recordings 
+
+### Keys (items)
+
+  `session_id`: "session_ge1nse2c",
+  `words": Transcription corresponding to t
+  `start_time`: Start time in second.
+  `end_time`: End time in second.
+  `speaker`: Speaker tagging in string: "speaker<N>"
+
+### Source Datasets
+
+The dataset combines entries from various sources:
+
+- **Development Sources**:
+  - `dev`: 142 sessions
+
+- **Evaluation Sources**:
+  - `eval`: 104 Sessions
+
+
+
+## Access
+
+The dataset can be accessed and downloaded through the HuggingFace Datasets library.
+
+
+## Evaluation
+
+This dataset can be evaluated by [MeetEval Software](https://github.com/fgnt/meeteval)
+
+### From PyPI
+```
+pip install meeteval
+```
+
+### From source
+```
+git clone https://github.com/fgnt/meeteval
+pip install -e ./meeteval
+```
+
+### Evaluate the corrected segLST files:
+```
+python -m meeteval.wer cpwer -h err_source_text/dev/session_ge1nse2c.json -r ref_annotate_text/dev/session_ge1nse2c.json
+```
+Or after installation, you can use the following command alternatively.
+```
+meeteval-wer cpwer -h err_source_text/dev/session_ge1nse2c.json -r ref_annotate_text/dev/session_ge1nse2c.json
+```
+
+### References
+
+```bib
+@inproceedings{park2024enhancing,
+  title={Enhancing speaker diarization with large language models: A contextual beam search approach},
+  author={Park, Tae Jin and Dhawan, Kunal and Koluguri, Nithin and Balam, Jagadeesh},
+  booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
+  pages={10861--10865},
+  year={2024},
+  organization={IEEE}
+}
+```
+
+```bib
+@InProceedings{MeetEval23,
+  title={MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems},
+  author={von Neumann, Thilo and Boeddeker, Christoph and Delcroix, Marc and Haeb-Umbach, Reinhold},
+  booktitle={CHiME-2023 Workshop, Dublin, England},
+  year={2023}
+}
+```