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--- |
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language: |
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- he |
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viewer: false |
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task_categories: |
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- text-to-speech |
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tags: |
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- tts |
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--- |
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# SASpeech |
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This dataset contains 13+ hours of speech in Hebrew of single speaker in `44.1khz |
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The metadata.csv contains `file_id|text|phonemes` |
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Where the file_id is the name of the file in `./wav` folder |
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The dataset is cleaned from numbers, it contains only Hebrew words. |
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Additional the words have Hebrew diacritics + phonetics marks (non standard) you may remove the non standard if you have use of the text. |
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The last column is phonemes created with [phonikud](https://phonikud.github.io) |
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Created from https://www.openslr.org/134 |
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## License |
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Non commercial use only. |
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See license in OpenSLR: https://www.openslr.org/134 |
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## Contents |
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The folder `saspeech_manual/` contains 3 hours (~7GB) with hand annotated transcripts |
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The folder `saspeech_automatic/` contains ~12 hours (~1GB) with automatic transcripts with ivrit.ai Whisper turbo and aggressive cleans (from 30 hours) |
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## LJSpeech format |
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To convert the data to LJSpeech format, use the following: |
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```python |
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import pandas as pd |
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df = pd.read_csv('metadata.csv', sep='\t', names=['file_id', 'text', 'phonemes']) |
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df[['file_id', 'phonemes']].to_csv('subset.csv', sep='|', header=False, index=False) |
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``` |
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## Resample |
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The dataset sample rate is 44.1khz |
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You can resample to 22.05khz with the following: |
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```python |
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from pydub import AudioSegment |
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from pathlib import Path |
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from tqdm import tqdm |
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in_dir = Path("wav") |
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out_dir = Path("wav_22050") |
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out_dir.mkdir(exist_ok=True) |
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for f in tqdm(list(in_dir.glob("*.wav"))): |
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audio = AudioSegment.from_wav(f) |
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audio = audio.set_frame_rate(22050).set_channels(1) |
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audio.export(out_dir / f.name, format="wav") |
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``` |
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## Setup |
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```console |
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uv pip install huggingface_hub |
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sudo apt install p7zip-full |
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uv run huggingface-cli download --repo-type dataset thewh1teagle/saspeech ./manual/saspeech_manual_v1.7z --local-dir . |
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7z x saspeech_v1.7z |
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``` |
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## Changelog saspeech manual |
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- v1: prepare files from manual transcript |
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- v2: enhance with Adobe enhance speech v2 and normalize to 22.05khz |
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- Add saspeech_short with auto generated short segments |
