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