Update librispeech_asr_test.py

librispeech_asr_test.py

@@ -16,9 +16,13 @@
 # Lint as: python3
 """Librispeech automatic speech recognition dataset."""
 
+from __future__ import absolute_import, division, print_function
+
+import glob
+import os
 
 import datasets
-from datasets.tasks import AutomaticSpeechRecognition
+
 
 
 _CITATION = """\
@@ -98,51 +102,34 @@ class LibrispeechASR(datasets.GeneratorBasedBuilder):
                     "id": datasets.Value("string"),
                 }
             ),
-            supervised_keys=("file", "text"),
+            supervised_keys=("speech", "text"),
             homepage=_URL,
             citation=_CITATION,
-            task_templates=[AutomaticSpeechRecognition(audio_file_path_column="file", transcription_column="text")],
         )
 
     def _split_generators(self, dl_manager):
-        archive_path = dl_manager.download(_DL_URLS[self.config.name])
-
-
-        return  [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST, gen_kwargs={"files": dl_manager.iter_archive(archive_path["test"])}
-            ),
+        archive_path = dl_manager.download_and_extract(_DL_URLS[self.config.name])
+        return [
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"archive_path": archive_path["dev"], "split_name": f"dev_{self.config.name}"}),
         ]
 
-    def _generate_examples(self, files):
-        """Generate examples from a LibriSpeech archive_path."""
-        key = 0
-        audio_data = {}
-        transcripts = []
-        for path, f in files:
-            if path.endswith(".flac"):
-                id_ = path.split("/")[-1][: -len(".flac")]
-                audio_data[id_] = f.read()
-            elif path.endswith(".trans.txt"):
+    def _generate_examples(self, archive_path, split_name):
+        """Generate examples from a Librispeech archive_path."""
+        transcripts_glob = os.path.join(archive_path, split_name, "*/*/*.txt")
+        for transcript_file in glob.glob(transcripts_glob):
+            path = os.path.dirname(transcript_file)
+            with open(os.path.join(path, transcript_file)) as f:
                 for line in f:
-                    if line:
-                        line = line.decode("utf-8").strip()
-                        id_, transcript = line.split(" ", 1)
-                        audio_file = f"{id_}.flac"
-                        speaker_id, chapter_id = [int(el) for el in id_.split("-")[:2]]
-                        transcripts.append(
-                            {
-                                "id": id_,
-                                "speaker_id": speaker_id,
-                                "chapter_id": chapter_id,
-                                "file": audio_file,
-                                "text": transcript,
-                            }
-                        )
-            if audio_data and len(audio_data) == len(transcripts):
-                for transcript in transcripts:
-                    audio = {"path": transcript["file"], "bytes": audio_data[transcript["id"]]}
-                    yield key, {"audio": audio, **transcript}
-                    key += 1
-                audio_data = {}
-                transcripts = []
+                    line = line.strip()
+                    key, transcript = line.split(" ", 1)
+                    audio_file = f"{key}.flac"
+                    speaker_id, chapter_id = [int(el) for el in key.split("-")[:2]]
+                    example = {
+                        "id": key,
+                        "speaker_id": speaker_id,
+                        "chapter_id": chapter_id,
+                        "file": os.path.join(path, audio_file),
+                        "audio": os.path.join(path, audio_file),
+                        "text": transcript,
+                    }
+                    yield key, example