ts support

babelbox_voice.py

@@ -7,6 +7,8 @@ import datasets
 from typing import List
 from pathlib import Path
 from tqdm import tqdm
+import torchaudio
+from io import BytesIO
 logger = datasets.logging.get_logger(__name__)
 
 _CITATION = """\
@@ -68,7 +70,7 @@ class BabelboxVoice(datasets.GeneratorBasedBuilder):
                 {
                     "path": datasets.Value("string"),
                     "audio": datasets.features.Audio(sampling_rate=16_000),
-                    "sentence": datasets.Value("string"),
+                    "text": datasets.Value("binary"),
                     "speaker_id": datasets.Value("string"),
                     "sex": datasets.Value("string"),
                     "accent": datasets.Value("string"),
@@ -79,7 +81,7 @@ class BabelboxVoice(datasets.GeneratorBasedBuilder):
                 {
                     "path": datasets.Value("string"),
                     "audio": datasets.features.Audio(sampling_rate=16_000),
-                    "sentence": datasets.Value("string"),
+                    "text": datasets.Value("binary"),
                     "speaker_id": datasets.Value("string"),
                     "sex": datasets.Value("string"),
                     "accent": datasets.Value("string"),
@@ -150,6 +152,11 @@ class BabelboxVoice(datasets.GeneratorBasedBuilder):
             def filter_sentence(sentence):
                 if "... tyst under denna inspelning ..." in  sentence: return False
                 return True
+            
+            def get_audio(file):
+                file_buf = BytesIO(file.read())
+                array, audio_sr = torchaudio.load(file_buf, format="wav")
+                return array[0], audio_sr
                               
             for i, audio_archive in enumerate(archives):
                 for path, file in audio_archive:
@@ -158,12 +165,25 @@ class BabelboxVoice(datasets.GeneratorBasedBuilder):
                         
                     metadata_item = metadata[path] 
                     
+                    audio_array, audio_sr = get_audio(file)
+                        
                     if filter_sentence(metadata_item['sentence']) == False: continue
+                    
+                    audio_len = len(audio_array) / sampling_rate
+                    audio_len = round(audio_len / 2, 2) * 2
+                    
+                    text = {
+                        "text": metadata_item['sentence'],
+                        "offsets": [ 
+                            {"text": metadata_item['sentence'], "timestamp": (0.0, audio_len) }
+                        ]
+                    }
+                    
                 
                     result = {
                         'path' : path,
-                        'audio' : {"path": path, "bytes": file.read(), "sampling_rate": sampling_rate },
-                        'sentence' : metadata_item['sentence'],
+                        'audio': {"path": path, "array": audio_array, "sampling_rate": sampling_rate},
+                        'text' : text,
                         'speaker_id' : metadata_item['speaker_id'],
                         'sex' : metadata_item['sex'],
                         'accent' : metadata_item['accent']