language:
- fa
task_categories:
- automatic-speech-recognition
- text-to-speech
- text-to-speech
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
- name: Length (seconds)
dtype: int64
splits:
- name: train
num_bytes: 368910411.993
num_examples: 2101
download_size: 365903240
dataset_size: 368910411.993
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- Benchmark
- Speech
- STT
- ASR
This dataset consists of 3 hours of 16kHz audio collected from diverse environments to better represent real-world scenarios. The recordings were sourced from audiobooks, YouTube, and other public sources, ensuring a wide variety of speech styles and acoustic conditions.
One key advantage of this dataset is that it was collected from recent sources within the last few months, ensuring no overlap with training data and fairness for evaluating other STT models.
To enable a robust and fair comparison of models, the dataset has been carefully normalized: extra characters and inconsistencies in Persian text have been removed, and orthographic variations have been standardized.
For a detailed explanation of the normalization process, please refer to our GitHub page.
We specialize in cutting-edge Voice & Audio Intelligence—from state-of-the-art Speech-to-Text (STT) and natural Text-to-Speech (TTS) to Voice Verification, Audio Intelligence, and domain-adapted LLMs.
Need higher accuracy, lower latency, or custom-trained voice models for your enterprise?
📬 Contact Sales: info@c1tech.group
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