Create dataseting.py

dataseting.py

@@ -0,0 +1,94 @@
+import json
+
+# Define a function to create a dataset with unique names
+def create_voice_model_dataset(num_names):
+    # Generate a dataset with unique names
+    dataset = {"voiceModels": []}
+    
+    for i in range(1, num_names + 1):
+        voice_model = {
+            "name": f"VoiceModel_{i}",
+            "description": f"Description for Voice Model {i}",
+            "version": "1.0",
+            "language": "en-US",
+            "voiceSettings": {
+                "gender": "neutral",
+                "age": "adult",
+                "accent": "American",
+                "tone": "natural",
+                "speakingRate": 1.0,
+                "volumeGain": 0.0
+            },
+            "speechSynthesis": {
+                "voiceName": f"VoiceModel_{i}_Voice",
+                "sampleRateHertz": 24000,
+                "pitch": 1.0,
+                "range": {
+                    "min": 80,
+                    "max": 250
+                },
+                "intelligibility": 0.8,
+                "emotionalTone": {
+                    "happy": 0.6,
+                    "sad": 0.3,
+                    "angry": 0.2,
+                    "neutral": 0.9
+                }
+            },
+            "phoneticModels": [
+                {
+                    "name": f"VoiceModel_{i}_Phonetic_Model",
+                    "description": "Basic phonetic model for standard American English pronunciation.",
+                    "phonemes": [
+                        "AA", "AE", "AH", "AO", "AW", "AY", "B", "CH", "D", "DH", "EH", "ER", "EY", "F", "G", "HH", "IH", "IY", "JH", "K", "L", "M", "N", "NG", "OW", "OY", "P", "R", "S", "SH", "T", "TH", "UH", "UW", "V", "W", "Y", "Z", "ZH"
+                    ]
+                }
+            ],
+            "sampleVoices": [
+                {
+                    "name": f"VoiceModel_{i}_Sample_Voice_1",
+                    "description": "Sample voice for formal contexts.",
+                    "gender": "male",
+                    "age": "adult",
+                    "audioFiles": [
+                        f"sample_{i}_1.wav",
+                        f"sample_{i}_2.wav",
+                        f"sample_{i}_3.wav"
+                    ]
+                },
+                {
+                    "name": f"VoiceModel_{i}_Sample_Voice_2",
+                    "description": "Sample voice for informal contexts.",
+                    "gender": "female",
+                    "age": "adult",
+                    "audioFiles": [
+                        f"sample_{i}_4.wav",
+                        f"sample_{i}_5.wav",
+                        f"sample_{i}_6.wav"
+                    ]
+                }
+            ],
+            "performanceMetrics": {
+                "accuracy": 0.95,
+                "latency": "100ms",
+                "responseTime": "250ms"
+            },
+            "additionalFeatures": {
+                "emotionRecognition": True,
+                "contextualAdaptation": True,
+                "multiLanguageSupport": False
+            }
+        }
+        dataset["voiceModels"].append(voice_model)
+
+    return dataset
+
+# Create the dataset
+num_names = 4000
+dataset = create_voice_model_dataset(num_names)
+
+# Save the dataset to a JSON file
+with open('voice_model_dataset.json', 'w') as f:
+    json.dump(dataset, f, indent=4)
+
+print(f"Dataset with {num_names} voice models has been created and saved to 'voice_model_dataset.json'.")