Codyfederer/test3434234
test3434234 This is a merged speech dataset containing 848 audio segments from 2 source datasets. Dataset Information Total Segments: 848 Speakers: 2 Languages: tr Emotions: angry, happy, neutral Original Datasets: 2 Dataset Structure Each example contains: audio: Audio file (WAV format, original sampling rate preserved) text: Transcription of the audio speaker_id: Unique speaker identifier (made unique across all merged datasets) emotion:… See the full description on the dataset page: https://huggingface.co/datasets/Codyfederer/test3434234.
test3434234
This is a merged speech dataset containing 848 audio segments from 2 source datasets.
Dataset Information
- Total Segments: 848
- Speakers: 2
- Languages: tr
- Emotions: angry, happy, neutral
- Original Datasets: 2
Dataset Structure
Each example contains:
audio: Audio file (WAV format, original sampling rate preserved)text: Transcription of the audiospeaker_id: Unique speaker identifier (made unique across all merged datasets)emotion: Detected emotion (neutral, happy, sad, etc.)language: Language code (en, es, fr, etc.)
Usage
Loading the Dataset
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("Codyfederer/test3434234")
# Access the training split
train_data = dataset["train"]
# Example: Get first sample
sample = train_data[0]
print(f"Text: {sample['text']}")
print(f"Speaker: {sample['speaker_id']}")
print(f"Language: {sample['language']}")
print(f"Emotion: {sample['emotion']}")
# Play audio (requires audio libraries)
# sample['audio']['array'] contains the audio data
# sample['audio']['sampling_rate'] contains the sampling rateAlternative: Load from JSONL
from datasets import Dataset, Audio, Features, Value
import json
# Load the JSONL file
rows = []
with open("data.jsonl", "r", encoding="utf-8") as f:
for line in f:
rows.append(json.loads(line))
features = Features({
"audio": Audio(sampling_rate=None),
"text": Value("string"),
"speaker_id": Value("string"),
"emotion": Value("string"),
"language": Value("string")
})
dataset = Dataset.from_list(rows, features=features)Dataset Structure
The dataset includes:
data.jsonl- Main dataset file with all columns (JSON Lines)*.wav- Audio files underaudio_XXX/subdirectoriesload_dataset.txt- Python script for loading the dataset (rename to .py to use)
JSONL keys:
audio: Relative audio path (e.g.,audio_000/segment_000000_speaker_0.wav)text: Transcription of the audiospeaker_id: Unique speaker identifieremotion: Detected emotionlanguage: Language code
Speaker ID Mapping
Speaker IDs have been made unique across all merged datasets to avoid conflicts. For example:
- Original Dataset A:
speaker_0,speaker_1 - Original Dataset B:
speaker_0,speaker_1 - Merged Dataset:
speaker_0,speaker_1,speaker_2,speaker_3
Original dataset information is preserved in the metadata for reference.
Data Quality
This dataset was created using the Vyvo Dataset Builder with:
- Automatic transcription and diarization
- Quality filtering for audio segments
- Music and noise filtering
- Emotion detection
- Language identification
License
This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Citation
@dataset{vyvo_merged_dataset,
title={test3434234},
author={Vyvo Dataset Builder},
year={2025},
url={https://huggingface.co/datasets/Codyfederer/test3434234}
}This dataset was created using the Vyvo Dataset Builder tool.
