up

peoples_speech-clean.py

@@ -72,6 +72,10 @@ _N_SHARDS_URL = _BASE_URL + "n_shards.json"
 # relative path to metadata inside dataset's repo
 _MANIFEST_URL = _BASE_URL + "{split}/{config}.json"
 
+_WHISPER_TRANSCRIPT_URL = "https://huggingface.co/datasets/distil-whisper/peoples_speech-clean/resolve/main/transcription_data/greedy_search/"
+
+_WHISPER_TRANSCRIPT_URLs = _WHISPER_TRANSCRIPT_URL + "/{split}-transcription.txt"
+
 
 class PeoplesSpeechConfig(datasets.BuilderConfig):
 
@@ -104,6 +108,7 @@ class PeoplesSpeech(datasets.GeneratorBasedBuilder):
                     "audio": datasets.Audio(sampling_rate=16_000),
                     "duration_ms": datasets.Value("int32"),
                     "text": datasets.Value("string"),
+                    "whisper_transcript": datasets.Value("string"),
                 }
             ),
             task_templates=[AutomaticSpeechRecognition()],
@@ -113,6 +118,8 @@ class PeoplesSpeech(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
+        if self.config.name not in ["clean", "validation", "test"]:
+            raise ValueError("This dataset is only compatible with the `clean` config.")
 
         if self.config.name == "microset":
             # take only first data archive for demo purposes
@@ -157,13 +164,16 @@ class PeoplesSpeech(datasets.GeneratorBasedBuilder):
         # In non-streaming mode, we extract the archives to have the data locally:
         local_extracted_archive_paths = dl_manager.extract(audio_archive_paths) \
             if not dl_manager.is_streaming else \
-            {split: [None] * len(audio_archive_paths) for split in splits_to_configs}
+            {split: [None] * len(audio_archive_paths[split]) for split in splits_to_configs}
 
         manifest_urls = {
             split: _MANIFEST_URL.format(split=split, config=config) for split, config in splits_to_configs.items()
         }
         manifest_paths = dl_manager.download_and_extract(manifest_urls)
 
+        transcription_urls = {split: _WHISPER_TRANSCRIPT_URLs.format(split=split) for split in splits_to_configs}
+        transcript_archive_path = dl_manager.download(transcription_urls)
+
         # To access the audio data from the TAR archives using the download manager,
         # we have to use the dl_manager.iter_archive method
         #
@@ -188,13 +198,14 @@ class PeoplesSpeech(datasets.GeneratorBasedBuilder):
                         # use iter_archive here to access the files in the TAR archives:
                         "archives": [dl_manager.iter_archive(path) for path in audio_archive_paths[split]],
                         "manifest_path": manifest_paths[split],
+                        "whisper_transcript": transcript_archive_path[split],
                     }
                 )
             )
 
         return split_generators
 
-    def _generate_examples(self, local_extracted_archive_paths, archives, manifest_path):
+    def _generate_examples(self, local_extracted_archive_paths, archives, manifest_path, whisper_transcript):
         meta = dict()
         with open(manifest_path, "r", encoding="utf-8") as f:
             for line in tqdm(f, desc="reading metadata file"):
@@ -211,6 +222,15 @@ class PeoplesSpeech(datasets.GeneratorBasedBuilder):
                         "duration_ms": duration
                     }
 
+        whisper_transcripts = []
+
+        with open(whisper_transcript, encoding="utf-8") as f:
+            for row in f:
+                whisper_transcripts.append(row.rstrip("\n"))
+
+        idx = 0
+
+
         for local_extracted_archive_path, archive in zip(local_extracted_archive_paths, archives):
             # Here we iterate over all the files within the TAR archive:
             for audio_filename, audio_file in archive:
@@ -223,5 +243,7 @@ class PeoplesSpeech(datasets.GeneratorBasedBuilder):
                     "id": audio_filename,
                     "audio": {"path": path, "bytes": audio_file.read()},
                     "text": meta[audio_filename]["text"],
-                    "duration_ms": meta[audio_filename]["duration_ms"]
+                    "duration_ms": meta[audio_filename]["duration_ms"],
+                    "whisper_transcript": whisper_transcripts[idx],
                 }
+                idx += 1