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--- |
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dataset_info: |
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features: |
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- name: audio |
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dtype: audio |
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- name: text |
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dtype: string |
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- name: duration |
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dtype: float64 |
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- name: token_count |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 5374523458.74 |
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num_examples: 11444 |
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- name: dev |
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num_bytes: 338070338 |
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num_examples: 648 |
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- name: test |
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num_bytes: 470470140 |
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num_examples: 899 |
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download_size: 13334454656 |
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dataset_size: 6183063936.74 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: dev |
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path: data/dev-* |
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- split: test |
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path: data/test-* |
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license: apache-2.0 |
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task_categories: |
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- automatic-speech-recognition |
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- text-to-audio |
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language: |
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- uz |
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pretty_name: FeruzaSpeech |
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size_categories: |
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- 10K<n<100K |
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--- |
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# FeruzaSpeech_to_fine_tuning |
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A speech corpus of **⏱️ ~59.1 total hours** of Uzbek audio paired with Latin‑script transcripts, intended for fine‑tuning ASR / speech‑to‑text models. |
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--- |
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## Dataset Details |
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### Dataset Description |
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This dataset contains recordings of native Uzbek speakers reading a mix of classical literature excerpts and school‑level writing prompts: |
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- **001**: Choliqushi (a novel by Rashod Nuri Guntekin, trans. by Mirzakalon Ismoiliy; first pub. Sept 1900). |
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- **002**: Excerpts from Uzbek secondary‑school essays (“To‘rtinchi sinfda edim…”, “Hayotdagi ilk xotiralaringizni yozing…”). |
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- ..... |
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Each line in `text_latin.txt` is of the form: |
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// |
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We strip the filename prefix in preprocessing so that the `text` field contains only the spoken words. |
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### Dataset Statistics |
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| Split | # Examples | Total Size | Approx. Duration | |
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|-------|-----------:|-----------:|-----------------:| |
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| train | 11 444 | 5.37 GB | 52.09 hours | |
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| dev | 648 | 0.34 GB | 2.93 hours | |
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| test | 899 | 0.47 GB | 4.08 hours | |
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## Dataset Creation |
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### Curation Rationale |
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We aim to provide a high‑quality, publicly available Uzbek ASR dataset combining both literary and educational domains to improve model robustness. |
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### Source Data |
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- Audio recorded in a quiet home‑studio environment, 16 kHz mono WAV, 16‑bit PCM. |
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- Transcripts created from existing texts (classical novels, school writing prompts). |
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### Who Are the Source Data Producers? |
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- **Recordings & Transcriptions by:** k2speech/FeruzaSpeech |
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- **Translators / Editors:** Nickoo 004 |
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## Uses |
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### Direct Use |
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Fine‑tuning or evaluating speech‑to‑text/ASR models for Uzbek. It’s also suitable for speech processing research (voice activity detection, speaker diarization, etc.). |
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### Out‑of‑Scope Use |
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- Speaker identification / sensitive demographic inference. |
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- Real‑time speech generation. |
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## Supported Tasks and Leaderboards |
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- **Task:** Automatic Speech Recognition |
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## Dataset Structure |
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Each example has the following fields: |
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- `audio`: an `Audio` object (`array` + `sampling_rate`) |
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- `text`: Latin‑script transcript, cleaned of filename tokens |
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- `duration`: audio length in seconds |
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- `token_count`: length of the transcript in raw word‑piece tokens |
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## Distribution |
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- **License:** Apache 2.0 |
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- **Repository:** https://huggingface.co/datasets/nickoo004/FeruzaSpeech_to_fine_tuning |
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## Who Maintains This Dataset |
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- **Created and maintained by:** Nickoo 004 |
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- **Last updated:** 2025‑05‑02 |
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- **Contact & Social:** |
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- Email: nursultankoshekbaev477@gmail.com |
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## Citation |
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If you use this dataset, please cite: |
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```bibtex |
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@misc{feruzaspeech2025, |
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title = {FeruzaSpeech\_to\_fine\_tuning: An Uzbek ASR Dataset}, |
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author = {Nickoo\, 004}, |
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year = {2025}, |
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howpublished = {\url{https://huggingface.co/datasets/nickoo004/FeruzaSpeech_to_fine_tuning}}, |
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license = {Apache 2.0} |
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} |
