Update README.md

README.md

@@ -92,11 +92,11 @@ using the VTT timestamps.
 | Field        | Type              | Description                                             |
 |--------------|-------------------|---------------------------------------------------------|
 | `id`         | `string`          | Unique segment id: `<talk_stem>_<index>` (e.g. `14zpc3Nj_e4_0003`) |
-| `talk_id`    | `string`          | Source talk file stem                                   |
-| `segment_id` | `int32`           | 0-based index of the segment within its talk            |
 | `audio`      | `Audio`           | Audio float32 waveform of the segment                    |
-| `duration`   | `float32`         | Duration of the audio segment **in seconds**            |
 | `transcript` | `string`          | Transcription text from the VTT file                    |
+| `duration`   | `float32`         | Duration of the audio segment **in seconds**            |
+| `talk_id`    | `string`          | Source talk file stem                                   |
+| `segment_id` | `int32`           | 0-based index of the segment within its talk            |
 | `start`      | `float32`         | Segment start time within the source talk (seconds)     |
 | `end`        | `float32`         | Segment end time within the source talk (seconds)       |
 
@@ -120,18 +120,18 @@ ds = load_dataset("deepdml/mtedx", "ar", split="train")
 print(ds[0])
 # {
 #   'id':         '14zpc3Nj_e4_0001',
-#   'talk_id':    '14zpc3Nj_e4',
-#   'segment_id': 1,
 #   'audio':      {'array': array([...], dtype=float32), 'sampling_rate': 16000},
-#   'duration':   4.16,
 #   'transcript': 'أكل العالم وغص بنخلة',
+#   'duration':   4.16,
+#   'talk_id':    '14zpc3Nj_e4',
+#   'segment_id': 1,
 #   'start':      9.332,
 #   'end':        13.492,
 #   'language':   'ar'
 # }
 
 # Stream a large language without downloading everything
-ds = load_dataset("your-username/mtedx", "es", split="train", streaming=True)
+ds = load_dataset("deepdml/mtedx", "es", split="train", streaming=True)
 for sample in ds:
     audio = sample["audio"]["array"]           # numpy float32 array @ 16 kHz
     text  = sample["transcript"]
@@ -139,7 +139,7 @@ for sample in ds:
     break
 
 # ASR fine-tuning example (Whisper / wav2vec2)
-ds = load_dataset("your-username/mtedx", "fr", split="train")
+ds = load_dataset("deepdml/mtedx", "fr", split="train")
 ds = ds.select_columns(["audio", "transcript", "duration"])
 ```