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Implementation:Speechbrain Speechbrain Prepare KsponSpeech

From Leeroopedia


Knowledge Sources
Domains Speech_Recognition, Data_Preparation
Last Updated 2026-02-09 00:00 GMT

Overview

Concrete tool for preparing the KsponSpeech dataset for automatic speech recognition provided by the SpeechBrain library.

Description

This script creates CSV data manifest files for the KsponSpeech (Korean Spontaneous Speech) dataset. It processes raw audio files and transcriptions, generates per-split CSV files with audio paths, durations, and transcripts, and supports merging multiple splits into a single CSV. The script handles Korean text normalization and is designed for the transformer-based ASR recipe.

Usage

Use this when preparing the KsponSpeech dataset for Korean ASR training with SpeechBrain recipes.

Code Reference

Source Location

Signature

def prepare_ksponspeech(
    data_folder,
    save_folder,
    tr_splits=[],
    dev_splits=[],
    te_splits=[],
    select_n_sentences=None,
    merge_lst=[],
    merge_name=None,
    skip_prep=False,
):

Import

from recipes.KsponSpeech.ASR.transformer.ksponspeech_prepare import prepare_ksponspeech

I/O Contract

Inputs

Name Type Required Description
data_folder str Yes Path to the folder where the original KsponSpeech dataset is stored
save_folder str Yes Directory where CSV files will be stored
tr_splits list No List of train splits (e.g. ['train', 'dev', 'eval_clean', 'eval_other'])
dev_splits list No List of dev splits (e.g. ['dev'])
te_splits list No List of test splits (e.g. ['eval_clean', 'eval_other'])
select_n_sentences int No If set, only use this many sentences (default: None)
merge_lst list No List of splits to merge into a single CSV file
merge_name str No Name of the merged CSV file
skip_prep bool No If True, skip data preparation (default: False)

Outputs

Name Type Description
{split}.csv CSV Per-split manifest files with audio paths, durations, and transcriptions
{merge_name}.csv CSV Optionally merged CSV combining multiple splits

Usage Examples

from recipes.KsponSpeech.ASR.transformer.ksponspeech_prepare import prepare_ksponspeech

prepare_ksponspeech(
    data_folder="/path/to/KsponSpeech",
    save_folder="/path/to/output",
    tr_splits=["train"],
    dev_splits=["dev"],
    te_splits=["eval_clean", "eval_other"],
)

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