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README.md

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+# Combined Fine-tuned Sesame CSM 1B Synthetic Speech Dataset
+
+## Data Format
+
+Each sample contains:
+- **audio**: Audio array with sampling_rate (24kHz)
+- **text**: Original transcript text
+- **speaker_id**: Speaker identifier (F04, M02, FC02, MC01, F02, M04, 211, 4014)
+- **corpus**: Source corpus (TORGO, UA-Speech, LibriSpeech)
+- **condition**: Speaker condition (Dysarthric, Healthy)
+- **model_name**: Fine-tuned model name
+- **model_type**: "sesame_csm_1b_adapter"
+- **base_model**: Base model used (unsloth/csm-1b)
+- **adapter_path**: HuggingFace adapter path
+- **duration**: Audio duration in seconds
+- **sample_rate**: Audio sample rate (24000)
+- **sample_index**: Sample index number
+- **audio_file**: Original audio filename
+- **generated_at**: Generation timestamp
+
+## Usage Example
+
+```python
+from datasets import Dataset
+import pandas as pd
+
+# Load combined dataset
+dataset = Dataset.from_parquet("sesame_tts_synthetic_combined.parquet")
+
+print(f"Total samples: {len(dataset)}")
+print(f"Speakers: {set(dataset['speaker_id'])}")
+
+# Filter by model type
+sesame_samples = dataset.filter(lambda x: x['model_type'] == 'sesame_csm_1b_adapter')
+print(f"Sesame CSM samples: {len(sesame_samples)}")
+
+# Filter by condition
+dysarthric_samples = dataset.filter(lambda x: x['condition'] == 'Dysarthric')
+healthy_samples = dataset.filter(lambda x: x['condition'] == 'Healthy')
+
+print(f"Dysarthric: {len(dysarthric_samples)}, Healthy: {len(healthy_samples)}")
+
+# Play sample
+sample = dataset[0]
+from IPython.display import Audio
+Audio(sample['audio']['array'], rate=sample['audio']['sampling_rate'])
+
+# Convert to DataFrame for analysis
+df = dataset.to_pandas()
+print(df.groupby(['corpus', 'condition'])['duration'].agg(['count', 'sum', 'mean']))
+```
+ 

dataset_info.json

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+{
+  "dataset_name": "combined_sesame_tts_synthetic",
+  "dataset_size": 759,
+  "description": "Combined fine-tuned Sesame CSM 1B synthetic speech dataset with LoRA adapters for pathological speech from 8 speakers",
+  "speakers": {
+    "MC01": {
+      "name": "TORGO Healthy Male",
+      "corpus": "TORGO",
+      "condition": "Healthy",
+      "gender": "Male",
+      "samples": 97,
+      "adapter_path": "resproj007/torgo_healthy_male_sesame_1b_MC01"
+    },
+    "FC02": {
+      "name": "TORGO Healthy Female",
+      "corpus": "TORGO",
+      "condition": "Healthy",
+      "gender": "Female",
+      "samples": 98,
+      "adapter_path": "resproj007/torgo_healthy_female_sesame_1b_FC02"
+    },
+    "F02": {
+      "name": "UA-Speech Female",
+      "corpus": "UA-Speech",
+      "condition": "Dysarthric",
+      "gender": "Female",
+      "samples": 182,
+      "adapter_path": "resproj007/uaspeech_female_sesame_1b_F02"
+    },
+    "M04": {
+      "name": "UA-Speech Male",
+      "corpus": "UA-Speech",
+      "condition": "Dysarthric",
+      "gender": "Male",
+      "samples": 184,
+      "adapter_path": "resproj007/uaspeech_male_sesame_1b_M04"
+    },
+    "4014": {
+      "name": "LibriSpeech Male",
+      "corpus": "LibriSpeech",
+      "condition": "Healthy",
+      "gender": "Male",
+      "samples": 30,
+      "adapter_path": "resproj007/librispeech_male_sesame_1b_4014"
+    },
+    "M02": {
+      "name": "TORGO Dysarthric Male",
+      "corpus": "TORGO",
+      "condition": "Dysarthric",
+      "gender": "Male",
+      "samples": 69,
+      "adapter_path": "resproj007/torgo_dysarthric_male_sesame_1b_M02"
+    },
+    "F04": {
+      "name": "TORGO Dysarthric Female",
+      "corpus": "TORGO",
+      "condition": "Dysarthric",
+      "gender": "Female",
+      "samples": 69,
+      "adapter_path": "resproj007/torgo_dysarthric_female_sesame_1b_F04"
+    },
+    "211": {
+      "name": "LibriSpeech Female",
+      "corpus": "LibriSpeech",
+      "condition": "Healthy",
+      "gender": "Female",
+      "samples": 30,
+      "adapter_path": "resproj007/librispeech_female_sesame_1b_211"
+    }
+  },
+  "corpora": [
+    "TORGO",
+    "UA-Speech",
+    "LibriSpeech"
+  ],
+  "conditions": [
+    "Dysarthric",
+    "Healthy"
+  ],
+  "model_info": {
+    "base_model": "unsloth/csm-1b",
+    "model_type": "sesame_csm_1b_adapter",
+    "fine_tuning_method": "lora_adapter",
+    "architecture": "sesame_csm_1b",
+    "training_corpora": [
+      "TORGO",
+      "UA-Speech",
+      "LibriSpeech"
+    ]
+  },
+  "audio_info": {
+    "sampling_rate": 24000,
+    "format": "wav",
+    "dtype": "float32",
+    "channels": 1
+  },
+  "features": {
+    "audio": {
+      "feature_type": "Audio",
+      "sampling_rate": 24000
+    },
+    "text": "string",
+    "speaker_id": "string",
+    "corpus": "string",
+    "condition": "string",
+    "model_name": "string",
+    "model_type": "string",
+    "base_model": "string",
+    "adapter_path": "string",
+    "duration": "float64",
+    "sample_rate": "int64",
+    "sample_index": "int64",
+    "audio_file": "string",
+    "generated_at": "string"
+  },
+  "statistics": {
+    "total_test_samples": 800,
+    "successfully_generated": 759,
+    "skipped_samples": 41,
+    "overall_success_rate": "94.9%",
+    "total_speakers": 8,
+    "total_duration_hours": 0.8077777777777778,
+    "avg_duration_per_sample": 3.831357048748353
+  },
+  "generation_info": {
+    "generated_date": "2025-09-14T15:08:08.091968",
+    "converter": "SesameTTSParquetConverter",
+    "version": "1.0",
+    "source_directory": "sesame_synthetic_data"
+  }
+}

sesame_tts_synthetic_combined.parquet

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+size 133589427