add missed row

README.md

@@ -15,10 +15,10 @@ dataset_info:
   config_name: all
   splits:
   - name: train
-    num_bytes: 40431494
-    num_examples: 157904
-  download_size: 5977562856
-  dataset_size: 40431494
+    num_bytes: 40431744
+    num_examples: 157905
+  download_size: 5977720839
+  dataset_size: 40431744
 ---
 
 # Dataset Card for OpenSLR Nepali Large ASR Cleaned
@@ -105,4 +105,4 @@ Nepali
 
 ### Data Splits
 
-The dataset is not split. The consumer should split it as per their requirements.
+The dataset is not split. The consumer should split it as per their requirements.

data/utt_spk_text.tsv

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:aeea4d61babd6e03583a5a6a976af9c03fcefd62f43bd05fa047cc469a353511
-size 10883731
+oid sha256:03d7ddf66ec8390bf1c35d6cf64afa8ecbf33db9bc5105304de48985db3bdb72
+size 11041714

openslr-nepali-asr-cleaned.py

@@ -118,10 +118,10 @@ class OpenslrNepaliAsrCleaned(datasets.GeneratorBasedBuilder):
         with open(index_file, encoding="utf-8") as f:
             reader = csv.DictReader(f, delimiter='\t')
             for key, row in enumerate(reader):
-                path = f"{audio_paths[row['Utterance'][0]]}/cleaned/asr_nepali/data/{row['Utterance'][:2]}/{row['Utterance']}.flac"
+                path = f"{audio_paths[row['utterance_id'][0]]}/cleaned/asr_nepali/data/{row['utterance_id'][:2]}/{row['utterance_id']}.flac"
                 yield key, {
-                    "utterance_id": row['Utterance'],
-                    "speaker_id": row['Speaker'],
+                    "utterance_id": row['utterance_id'],
+                    "speaker_id": row['speaker_id'],
                     "utterance": path,
-                    "transcription": row['Text'],
+                    "transcription": row['transcription'],
                 }