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README.md

@@ -1,28 +1,77 @@
----
-dataset_info:
-  features:
-  - name: audio_filepath
-    dtype: string
-  - name: text
-    dtype: string
-  - name: duration
-    dtype: float64
-  - name: source
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 714056846
-    num_examples: 2338349
-  - name: valid
-    num_bytes: 17109137
-    num_examples: 77068
-  download_size: 318399482
-  dataset_size: 731165983
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: valid
-    path: data/valid-*
----
+# Meta Speech Recognition English Dataset (v1)
+
+This dataset contains only the metadata (JSON/Parquet) for English speech recognition samples.  
+**Audio files are NOT included.**
+
+## Data Download Links
+
+- **CommonVoice:** [https://commonvoice.mozilla.org/en/datasets](https://commonvoice.mozilla.org/en/datasets)
+- **People's Speech:** [https://huggingface.co/datasets/MLCommons/peoples_speech](https://huggingface.co/datasets/MLCommons/peoples_speech)
+- **LibriSpeech:** 
+  - [train-clean-100](https://www.openslr.org/resources/12/train-clean-100.tar.gz)
+  - [train-clean-360](https://www.openslr.org/resources/12/train-clean-360.tar.gz)
+  - [train-other-500](https://www.openslr.org/resources/12/train-other-500.tar.gz)
+
+## Audio Directory Structure
+
+After downloading and extracting, organize your audio files as follows:
+
+- `/cv` for CommonVoice audio
+- `/peoplespeech_audio` for People's Speech audio
+- `/librespeech-en` for LibriSpeech audio
+
+## Mounting in NeMo Docker
+
+When running your NeMo ASR Docker container, mount the audio directories:
+
+```bash
+docker run -v /cv:/cv -v /peoplespeech_audio:/peoplespeech_audio -v /librespeech-en:/librespeech-en <nemo_docker_image>
+```
+
+## Splits and Sample Counts
+
+- **train**: 2338349 samples
+- **valid**: 77068 samples
+
+## Example Samples
+### train
+```json
+{
+  "audio_filepath": "/peoplespeech_audio/train-00769-of-00804_5.flac",
+  "text": "this is the same chart i just showed you a moment ago again seventy two percent is in good condition but what we found was that there were actually a decent amount of roads there so i had to surmount a sidewalk i'm sorry sidewalks that had were and very very good condition AGE_30_45 GER_MALE EMOTION_NEU INTENT_INFORM",
+  "duration": 14.8,
+  "source": "peoplespeech"
+}
+```
+```json
+{
+  "audio_filepath": "/peoplespeech_audio/train-00561-of-00804_1596.flac",
+  "text": "the board didn't rely on that theory and i guess what i was wondering is is it the board's conclusion that for some claims mr ENTITY_PERSON_NAME kit lens END alleged adverse acts were due to his military status whereas other AGE_30_45 GER_MALE EMOTION_NEU",
+  "duration": 14.65,
+  "source": "peoplespeech"
+}
+```
+
+### valid
+```json
+{
+  "audio_filepath": "/librespeech-en/train-other-500/177/122839/177-122839-0044.flac",
+  "text": "But after all, that's better than one of us being short and fat and the other tall and lean, like Morgan Sloane and his wife, Missus, Lynde says, it always makes her think of the long and short of it when she sees them together, well, said Anne to herself that night, as she brushed her hair before her gilt framed mirror. AGE_30_45 GER_FEMALE EMOTION_HAP INTENT_REFLECT",
+  "duration": 16.78,
+  "source": "librespeech-en"
+}
+```
+```json
+{
+  "audio_filepath": "/librespeech-en/train-clean-360/5637/41170/5637-41170-0009.flac",
+  "text": "The justice of the peace is over thirty ENTITY_DURATION miles END from me, For some matter of ENTITY_PRICE two roubles END, I should have to send a lawyer who costs me ENTITY_PRICE fifteen, END, and he related how a peasant had stolen some flour from the miller. AGE_45_60 GER_MALE EMOTION_NEU INTENT_EXPLAIN",
+  "duration": 12.51,
+  "source": "librespeech-en"
+}
+```
+
+
+## Usage
+
+Use the metadata in this repository for training or evaluation.  
+**Note:** You must ensure the `audio_filepath` in the metadata matches the path in your local or mounted directory.