datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
synthetic_dem
Dataset Card for synthetic_dem
Dataset Summary
The Synthetic DEM Corpus is the result of the first phase of a collaboration between El Colegio de México (COLMEX) and the Barcelona Supercomputing Center (BSC).
It all began when COLMEX was looking for a way to have its Diccionario del Español de México (DEM), which can be accessed online, include the option to play each of its words with a Mexican accent through synthetic speech files. On the other hand, BSC is always on… See the full description on the dataset page: https://huggingface.co/datasets/projecte-aina/synthetic_dem.barranquenho-ipa-dict-synthetic
Barranquenho IPA Pronunciation Dictionary
The first and only IPA pronunciation dictionary of Barranquenho — the
Ibero-Romance contact variety spoken in Barrancos (Baixo Alentejo, Portugal),
a mixed system born of centuries of Portuguese–Spanish (Extremaduran /
Andalusian) contact on the raia. Every headword is written in the
Convenção Ortográfica do Barranquenho (2025) orthography and paired with a
broad-phonemic IPA transcription plus Portuguese and Spanish glosses.
This… See the full description on the dataset page: https://huggingface.co/datasets/TigreGotico/barranquenho-ipa-dict-synthetic.multivoice-synthetic-speech
Synthetic Voice Samples · Africa
Synthetic speech. No human speaker was recorded for any clip in this dataset.
Generated with afrispeech-synth: text from
africa-corpus, normalised to a
universal orthography with africa-g2p, spoken by
Google Gemini's Live API.
17,010 clips · 38.8 hours · 566 languages · 30 voices
Every clip is a distinct sentence — no sentence is repeated
Each language is read by up to 30 different voices, one sentence per voice
~1.29 hours per voice… See the full description on the dataset page: https://huggingface.co/datasets/AfriSpeech/multivoice-synthetic-speech.synthetic_transcript_pt
Portuguese Speech Dataset with Multiple Training Configurations
A comprehensive Portuguese speech dataset offering three distinct training configurations for speech recognition research, each designed for different experimental scenarios and training paradigms.
🎯 Dataset Configurations Overview
This dataset provides three carefully curated subsets to enable comprehensive speech recognition research:
Configuration
Training Data
Validation
Test
Total Samples
Use Case… See the full description on the dataset page: https://huggingface.co/datasets/yuriyvnv/synthetic_transcript_pt.Synthetic-Medical-Speech-Dataset
Synthetic Medical Speech Dataset
Overview
Synthetic Medical Speech Dataset is a synthetic dataset of audio–text pairs designed for developing and evaluating automatic speech recognition (ASR) models in the medical domain.The corpus contains thousands of short audio clips generated from medically relevant text using a text-to-speech (TTS) system.Each clip is paired with its corresponding transcript.Because all content is synthetically produced, the dataset does not contain… See the full description on the dataset page: https://huggingface.co/datasets/Hani89/Synthetic-Medical-Speech-Dataset.masri_synthetic
Dataset Card for masri_synthetic
Dataset Summary
The MASRI-SYNTHETIC is a corpus made out of synthesized speech in Maltese. The text-to-speech (TTS) system utilized to produce the utterances was developed by the Research & Development Department of Crimsonwing p.l.c.
The sentences used to create the corpus were extracted from the MLRS Corpus, which is a corpus of written or transcribed Maltese divided into different genres, including: culture, news, academic, religion… See the full description on the dataset page: https://huggingface.co/datasets/MLRS/masri_synthetic.synthetic_transcript_nl
Dutch Synthetic Speech Transcripts
This dataset contains 34,898 synthetic Dutch speech samples generated using GPT-4o-mini for transcript creation and OpenAI's TTS-1 model for speech synthesis. It was designed to augment Automatic Speech Recognition (ASR) training for low-resource scenarios, matching the linguistic distribution of Common Voice 17.0 Dutch.
Dataset Description
Purpose
This dataset addresses the challenge of limited labeled speech data for Dutch… See the full description on the dataset page: https://huggingface.co/datasets/yuriyvnv/synthetic_transcript_nl.synthetic-tts
Munni — Hindi/English Synthetic TTS Voice Dataset
Single-speaker, code-mixed Hindi (Devanagari) + English speech dataset built for
XTTS-v2 fine-tuning. Domain is call-center / customer-support style dialogue
(warranty, billing, appointment scheduling), with scripted placeholder phone
numbers spoken digit-by-digit.
8,796 clips / 18.16 hours, 24 kHz mono 16-bit PCM
Split: train 8,621 / validation 175 (98/2, seed 42)
Duration per clip: mean 7.43s, min 3.18s, max 11.00s
Single… See the full description on the dataset page: https://huggingface.co/datasets/routsourav1729/synthetic-tts.arabic-english-code-switching-synthetic-asr
Synthetic Arabic-English Code-Switched Speech for ASR
This dataset contains synthetic speech generated for Egyptian Arabic-English code-switched automatic speech recognition. It is published separately from the human review annotations so the human audio remains in its upstream Hugging Face repository.
Configurations
Configuration
Train
Test
Publication status
synthetic
8,655
962
Contains 5,673 ArE-CSTD-derived texts; noncommercial/share-alike terms… See the full description on the dataset page: https://huggingface.co/datasets/abdo1819/arabic-english-code-switching-synthetic-asr.Hausa-Synthetic-ASR-Dataset-XTTSSynthetic Hausa ASR dataset generated using a fine-tuned version of the XTTS-v2 model.
Sample rate: 24kHz.
Total duration: 574 hours.
korean-full-duplex-synthetic-dataset-preview
Korean Full-Duplex Synthetic Dataset Preview
Overview
Public preview of a Korean full-duplex synthetic speech dataset. This
repository contains 100 conversations sampled from a corpus of 89,273
conversations (2,000.5 hours); it does not publish the full corpus audio.
Preview contents
100 conversation WAV files
data/representative.jsonl
24 kHz, mono, 16-bit PCM
Events: normal, barge_in, backchannel, cutoff_by_user
Annotation format… See the full description on the dataset page: https://huggingface.co/datasets/Wi-Fi/korean-full-duplex-synthetic-dataset-preview.Synthetic_Turkish_TTS_Data
Synthetic Turkish TTS Data
This dataset was created by generating synthetic Turkish text across multiple speech scenarios. The text was produced in the following domains: finance_master, cs_master, parcel_delivery, ecommerce, telecom, isp_support, technical_support, subscription, insurance, health_appointments, public_services, education_registration, and daily_speech.
These synthetic texts were then synthesized with a high-quality Turkish TTS model. The dataset is intended to be… See the full description on the dataset page: https://huggingface.co/datasets/Anilosan15/Synthetic_Turkish_TTS_Data.nepali-tts-synthetic-v2
Nepali TTS Synthetic v2
383,298 synthetic Nepali (ne) speech/text pairs, 24 kHz mono 16-bit WAV embedded
as-is (no re-encode, no resampling).
Generated by the synthetic_pipeline in milanakdj/TTS_training: Edge TTS
synthesis → optional voice conversion against a pool of 600 real multi-speaker
reference clips → ASR-based QC gate on character error rate.
Read this before training on it
Only 48% of rows are voice-converted. Each row carries a kept field
recording… See the full description on the dataset page: https://huggingface.co/datasets/milanakdj/nepali-tts-synthetic-v2.synthetic-speaker-diarization-dataset-fa-large-3000burmese-synthetic-speech-corpus
Burmese Synthetic Speech Corpus (DatarrX/burmese-synthetic-speech-corpus)
Overview
The Burmese Synthetic Speech Corpus is a high-fidelity, manually curated audio dataset specifically designed to advance Text-to-Speech (TTS) systems, speech recognition, and other audio-driven Machine Learning tasks for the Burmese (Myanmar) language.
Created by DatarrX, this dataset bridges the gap in low-resource speech technologies by providing highly natural, native-sounding… See the full description on the dataset page: https://huggingface.co/datasets/DatarrX/burmese-synthetic-speech-corpus.open-vi-dialog-synthetic-100h
OpenDialog Vietnamese Synthetic Dialogue 100h
Synthetic Vietnamese two-speaker dialogue for ZipVoice-Dialog experiments.
12,000 chunks
30 seconds per chunk
100.0 hours total
Each item contains S1/S2 speaker labels, turn timings, target text,
relationship, pronouns, environment, topic, mood, and source reference IDs.
Audio renderer: vLLM-Omni VoxCPM2
Audio format: mono WAV, 48 kHz, 30 seconds per chunk
This is a research dataset. Review the source/reference licensing and the… See the full description on the dataset page: https://huggingface.co/datasets/tsdocode/open-vi-dialog-synthetic-100h.synthetic-speech-diarization-ru
synthetic-speech-diarization-ru
Synthetic speech diarization dataset in Parquet format.
Dataset Details
Number of tracks: 2000
Sampling rate: 16000 Hz
Audio format: Embedded in Parquet files (Audio feature compatible)
Storage: Parquet format for efficient loading
Dataset Structure
The dataset contains audio tracks with speaker diarization annotations, stored directly in Parquet format.
Features
audio: Audio waveform (Audio feature with array and… See the full description on the dataset page: https://huggingface.co/datasets/ivkond/synthetic-speech-diarization-ru.synthetic-parallel-external
Synthetic Parallel EN↔LG — external
Voice-controlled synthetic parallel speech dataset for Luganda-English
speech-to-speech translation, generated by the Hibiki-Zero fine-tuning pipeline.
Generation
Component
Model
Translation
Sunbird/translate-nllb-3.3b-salt
TTS
Sunbird/orpheus-3b-tts-multilingual
English speakers: salt_eng_0001, salt_eng_0002, salt_eng_0003
Luganda speakers: salt_lug_0001, waxal_lug_0001, waxal_lug_0002, waxal_lug_0003, waxal_lug_0004… See the full description on the dataset page: https://huggingface.co/datasets/yigagilbert/synthetic-parallel-external.multilingual-synthetic-tts
Multilingual Synthetic TTS Dataset
🏆 Submitted to the Uncharted Data Challenge
hosted by Adaption Labs — credit to
Adaptive Data by Adaption for organizing the hackathon.
A large-scale synthetic multilingual speech dataset — 68,677 clips across
9 languages, generated with Qwen3-TTS-12Hz-1.7B-Base
using zero-shot voice cloning from 5 reference speakers.
Intended for training and evaluating TTS, ASR, voice conversion, and
multilingual speech models. Each clip is paired with the… See the full description on the dataset page: https://huggingface.co/datasets/Reubencf/multilingual-synthetic-tts.synthetic-speech-diarization-ru
synthetic-speech-diarization-ru
Synthetic speech diarization dataset in Parquet format.
Dataset Details
Number of tracks: 2000
Sampling rate: 16000 Hz
Audio format: Embedded in Parquet files (Audio feature compatible)
Storage: Parquet format for efficient loading
Dataset Structure
The dataset contains audio tracks with speaker diarization annotations, stored directly in Parquet format.
Features
audio: Audio waveform (Audio feature with array and… See the full description on the dataset page: https://huggingface.co/datasets/niobures/synthetic-speech-diarization-ru.burmese-synthetic-speech-corpus
Burmese Synthetic Speech Corpus (DatarrX/burmese-synthetic-speech-corpus)
Overview
The Burmese Synthetic Speech Corpus is a high-fidelity, manually curated audio dataset specifically designed to advance Text-to-Speech (TTS) systems, speech recognition, and other audio-driven Machine Learning tasks for the Burmese (Myanmar) language.
Created by DatarrX, this dataset bridges the gap in low-resource speech technologies by providing highly natural, native-sounding… See the full description on the dataset page: https://huggingface.co/datasets/hackerlim7/burmese-synthetic-speech-corpus.somali-asr-synthetic-youtube
Somali ASR Synthetic YouTube Dataset
A Somali-language speech dataset derived from YouTube audio, intended for training and evaluating automatic speech recognition (ASR) and speech-to-text (STT) models. Transcriptions were generated synthetically (silver-standard) via ASR bootstrapping.
Dataset Summary
Split
Samples
train
~4,393
validation
200
test
100
Total
~4,693
Language: Somali (so)
Audio format: WAV, 16 kHz, mono, 16-bit PCM
Total… See the full description on the dataset page: https://huggingface.co/datasets/IbrahimDayax/somali-asr-synthetic-youtube.Synthetic_Turkish_TTS_Data
Not: Bu veri setinin dokümantasyonu Türk yapay zeka topluluğuna katkı sağlamak amacıyla VeriPazarı tarafından Türkçeye çevrilmiştir. Orijinal veri seti Anilosan15 tarafından geliştirilmiş olup, VeriPazarı tarafından Türk AI ekosistemi için arşivlenmiştir.
🔗 Orijinal Kaynak: Anilosan15/Synthetic_Turkish_TTS_Data
🔗 Derleyen Platform: VeriPazarı
Sentetik Türkçe TTS Veri Seti (Synthetic Turkish TTS Data)
Bu veri seti, çoklu konuşma senaryoları üzerinden sentetik Türkçe metinler… See the full description on the dataset page: https://huggingface.co/datasets/Taklaxbr/Synthetic_Turkish_TTS_Data.synthetic-parallel-salt
Synthetic Parallel EN↔LG — salt
Voice-controlled synthetic parallel speech dataset for Luganda-English
speech-to-speech translation, generated by the Hibiki-Zero fine-tuning pipeline.
Generation
Component
Model
Translation
Sunbird/translate-nllb-3.3b-salt
TTS
Sunbird/orpheus-3b-tts-multilingual
English speakers: salt_eng_0001, salt_eng_0002, salt_eng_0003
Luganda speakers: salt_lug_0001, waxal_lug_0001, waxal_lug_0002, waxal_lug_0003, waxal_lug_0004… See the full description on the dataset page: https://huggingface.co/datasets/yigagilbert/synthetic-parallel-salt.samromur_syntheticSamrómur Synthetic consists of 72 hours of synthetized speech in Icelandic.Chichewa-Synthetic-ASR-DatasetSynthetic Chichewa ASR dataset generated using a fine-tuned version of the YourTTS model.
Sample rate: 24kHz.
Total duration: 550 hours.
Synthetic-Egy-Speech-Dataset
Synthetic Egyptian Speech Dataset
A curated dataset of 1000 Egyptian Arabic speech samples — the best audio selected across 4 TTS models for each prompt, with transcription text and quality metadata.
Dataset Description
Each entry contains:
id: Unique prompt identifier (e.g., egy_0001)
text: Egyptian Arabic transcription text
audio_path: Path to the best-selected .wav audio file
model: TTS model that produced the best audio (lahgtna, chatterbox_egyptian, egtts_v01, or… See the full description on the dataset page: https://huggingface.co/datasets/MohamedGomaa30/Synthetic-Egy-Speech-Dataset.synthetic-asr-vi
Synthetic ASR data — vi
Generated by Valsea-ASR/synthetic-data-pipeline.
Audio is synthetic (TTS), targeted as training data for downstream ASR finetuning.
Total audio: 50.7 hr across short (5s) and long (30s) length buckets,
each in clean and augmented variants.
Loading
from datasets import load_dataset
ds = load_dataset("<org>/synthetic-asr-vi", "short_clean")
print(ds["train"][0]["audio"]) # {"array": np.ndarray, "sampling_rate": 16000, "path": "..."}… See the full description on the dataset page: https://huggingface.co/datasets/silvermango9927/synthetic-asr-vi.deafbench-synthetic-v2
DeafBench synthetic-v2
DeafBench synthetic-v2 is a frozen, 25-sample benchmark specification for
testing whether automatic speech recognition systems preserve information that
matters in accessible captions. It keeps conventional word error rate separate
from typed critical-information recall so a plausible transcript cannot hide a
lost time, digit sequence, username, code, Wi-Fi name, or proper name.
This repository publishes the reference text and reproducibility metadata. It… See the full description on the dataset page: https://huggingface.co/datasets/kvjones0243/deafbench-synthetic-v2.Luo-Synthetic-ASR-DatasetSynthetic Dholuo ASR dataset generated using a fine-tuned version of the YourTTS model.
Sample rate: 24kHz.
Total duration: 775 hours.