Override with Parquet version

README.md

@@ -0,0 +1,18 @@
+---
+license: mit
+tags:
+- assamese
+- audio
+- physics
+- class10
+delimiter: "|"
+column_names:
+  - "file_name"
+  - "text"
+features:
+  - name: file_name
+    dtype: audio
+  - name: text
+    dtype: string
+---
+#Comming soon

README.md.bak

@@ -1,19 +0,0 @@
----
-license: mit
-tags:
-- assamese
-- audio
-- physics
-- class10
-dataset_info:
-  - config_name: default
-    features:
-      - name: audio
-        dtype: audio
-      - name: text
-        dtype: string
-    splits:
-      - name: train
-        num_bytes: 345981
-        num_examples: 8178
----

align.py

@@ -1,3 +1,4 @@
+## this file need nvidia gpu, use google colab or your local with nvidia gpu
 import stable_whisper
 import whisper
 import json

parquet_dataset/README.md

@@ -1,8 +0,0 @@
----
-license: mit
-tags:
-- assamese
-- audio
-- physics
-- class10
----

parquet_dataset/dataset_dict.json

@@ -1 +0,0 @@
-{"splits": ["train"]}

parquet_dataset/train/data-00000-of-00001.arrow

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-size 1748672

parquet_dataset/train/dataset_info.json

@@ -1,41 +0,0 @@
-{
-  "builder_name": "csv",
-  "citation": "",
-  "config_name": "default",
-  "dataset_name": "csv",
-  "dataset_size": 345981,
-  "description": "",
-  "download_checksums": {
-    "/Users/tuklu/ML/Voice-clonning/Datasets/1hr_demo/metadata.csv": {
-      "num_bytes": 296913,
-      "checksum": null
-    }
-  },
-  "download_size": 296913,
-  "features": {
-    "audio": {
-      "_type": "Audio"
-    },
-    "text": {
-      "dtype": "string",
-      "_type": "Value"
-    }
-  },
-  "homepage": "",
-  "license": "",
-  "size_in_bytes": 642894,
-  "splits": {
-    "train": {
-      "name": "train",
-      "num_bytes": 345981,
-      "num_examples": 8178,
-      "dataset_name": "csv"
-    }
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-  "version": {
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-    "major": 0,
-    "minor": 0,
-    "patch": 0
-  }
-}

parquet_dataset/train/state.json

@@ -1,13 +0,0 @@
-{
-  "_data_files": [
-    {
-      "filename": "data-00000-of-00001.arrow"
-    }
-  ],
-  "_fingerprint": "3d68c266a02cc011",
-  "_format_columns": null,
-  "_format_kwargs": {},
-  "_format_type": null,
-  "_output_all_columns": false,
-  "_split": "train"
-}

pyproject.toml

@@ -5,7 +5,6 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.11.9"
 dependencies = [
-    "datasets>=4.2.0",
     "pydub>=0.25.1",
     "tts>=0.22.0",
     "whisper>=1.1.10",

to_parquet.py

@@ -1,32 +0,0 @@
-from datasets import load_dataset, Audio
-import os
-
-# Define the output directory for the new Parquet files
-output_dir = "parquet_dataset"
-
-# Check if metadata.csv exists
-if not os.path.exists("metadata.csv"):
-    print("--- ERROR: 'metadata.csv' not found in the current directory. ---")
-    exit()
-
-print("Loading dataset from metadata.csv...")
-# Load the dataset using the CSV loader, specifying the separator and column names.
-dataset = load_dataset(
-    "csv",
-    data_files={"train": "metadata.csv"},
-    delimiter="|",
-    column_names=["audio", "text"],
-    header=None
-)
-
-print("Casting the audio column to the correct data type...")
-# Explicitly tell the library that the 'audio' column contains paths to audio files.
-# This will load the audio data itself.
-dataset = dataset.cast_column("audio", Audio())
-
-print(f"Saving dataset to Parquet format in the '{output_dir}' directory...")
-# This saves the processed dataset, including audio data, into the Parquet format.
-dataset.save_to_disk(output_dir)
-
-print("\nConversion complete.")
-print(f"Your new, optimized dataset is ready in the '{output_dir}' folder.")

uv.lock

@@ -12,7 +12,6 @@ name = "1hr-demo"
 version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
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     { name = "pydub" },
     { name = "tts" },
     { name = "whisper" },
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