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Datasets:
meldynamics
/
liepa-3

Tasks:
Automatic Speech Recognition
Text-to-Speech
Modalities:
Audio
Text
Formats:
parquet
Languages:
Lithuanian
Size:
1M - 10M
Tags:
audio
speech
lithuanian
lt
baltic-languages
speech-recognition
Libraries:
Datasets
Dask
Polars
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metadata 
dataset_info:
  - config_name: dial
    features:
      - name: audio
        dtype:
          audio:
            sampling_rate: 44100
      - name: text
        dtype: string
      - name: category
        dtype: string
      - name: speaker_id
        dtype: string
      - name: gender
        dtype: string
      - name: age_group
        dtype: string
      - name: lang_type
        dtype: string
      - name: source
        dtype: string
      - name: region
        dtype: string
      - name: county
        dtype: string
      - name: file_path
        dtype: string
      - name: file_hash
        dtype: string
      - name: segment_id
        dtype: string
      - name: start_ms
        dtype: int32
      - name: end_ms
        dtype: int32
      - name: duration_ms
        dtype: int32
    splits:
      - name: train
        num_bytes: 15484268762
        num_examples: 111970
    download_size: 15471775524
    dataset_size: 15484268762
  - config_name: phon
    features:
      - name: audio
        dtype:
          audio:
            sampling_rate: 44100
      - name: text
        dtype: string
      - name: phono
        dtype: string
      - name: category
        dtype: string
      - name: speaker_id
        dtype: string
      - name: gender
        dtype: string
      - name: age_group
        dtype: string
      - name: lang_type
        dtype: string
      - name: source
        dtype: string
      - name: region
        dtype: string
      - name: county
        dtype: string
      - name: file_path
        dtype: string
      - name: file_hash
        dtype: string
      - name: segment_id
        dtype: string
      - name: start_ms
        dtype: int32
      - name: end_ms
        dtype: int32
      - name: duration_ms
        dtype: int32
    splits:
      - name: train
        num_bytes: 67850344340.188
        num_examples: 1084228
    download_size: 67737728325
    dataset_size: 67850344340.188
configs:
  - config_name: dial
    data_files:
      - split: train
        path: dial/train-*
  - config_name: phon
    data_files:
      - split: train
        path: phon/train-*
  - config_name: read
    data_files:
      - split: train
        path: read/train-*
  - config_name: spon
    data_files:
      - split: train
        path: spon/train-*
license: cc-by-4.0
multilinguality: monolingual
source_datasets:
  - original
pretty_name: LIEPA-3 Lithuanian Speech Corpus
task_categories:
  - automatic-speech-recognition
  - text-to-speech
tags:
  - audio
  - speech
  - lithuanian
  - lt
  - baltic-languages
  - speech-recognition
  - asr
  - text-to-speech
  - tts
  - liepa
  - liepa-3
language_creators:
  - found
  - crowdsourced
task_ids: []
annotations_creators:
  - expert-generated
language:
  - lt
size_categories:
  - 1M<n<10M

LIEPA-3 — Lithuanian Speech Corpus

Didysis lietuvių kalbos garsynas (LIEPA-3)

License: CC BY 4.0 Language: Lithuanian Audio: 44.1 kHz FLAC

Table of Contents

Dataset Summary

LIEPA-3 is a large, open corpus of Lithuanian speech (~10,000 hours, ~7.5 million audio files) built for automatic speech recognition (ASR), text-to-speech (TTS) and linguistic research. It spans read, spontaneous, phonetically-annotated and dialectal speech recorded under a wide range of conditions (studio, dictaphone, radio, TV, telephone, audiobooks).

Official repository: the authoritative release is published in the CLARIN-LT repository — https://clarin-repo.lt/items/0a04648e-ba4e-4e6f-9161-a2d01e8e9fdb/full. This 🤗 dataset is a repackaging of that corpus for the datasets library.

Audio is stored once at its source quality — 44.1 kHz / 16-bit mono FLAC (lossless). Resample on the fly for your task (see below); there is no quality loss versus the source when downsampling to 16 kHz (ASR) or 24 kHz (TTS).

Supported Tasks

  • automatic-speech-recognition — transcribe Lithuanian speech (audio + text). Downsample to 16 kHz at load time.
  • text-to-speech — single/multi-speaker Lithuanian TTS. Filter by speaker_id, gender, source (e.g. Studio); resample to 22.05/24 kHz.
from datasets import load_dataset, Audio

ds = load_dataset("meldynamics/liepa-3", "dial", split="train")   # native 44.1 kHz

# ASR: 16 kHz on the fly (lossless downsample)
ds_asr = ds.cast_column("audio", Audio(sampling_rate=16000))

# TTS: 24 kHz
ds_tts = ds.cast_column("audio", Audio(sampling_rate=24000))

# stream without downloading everything:
ds = load_dataset("meldynamics/liepa-3", "dial", split="train", streaming=True)

Languages

Monolingual Lithuanian (lt). Transcripts are normalized to lower case without punctuation, except the dial part, which uses an extended phonetic/dialectal notation (stress ˈ ˌ, palatalization ', dialect vowels æ ə ɜ ē ɘ ɨ ā, ...).

Dataset Structure

Configurations (corpus parts)

Each corpus part is a config; load one with the name argument.

  • dial — Dialectal speech — regional varieties of Lithuanian. Transcripts use an extended phonetic/dialectal notation (stress marks, palatalization, dialect-specific vowels). One phrase per file.
  • phon — Phonetically annotated speech. Full recordings are sliced into phrases using the Praat TextGrid ortho (orthographic) tier; the grids' phono (phonetic-transcription) tier is aligned to each phrase by time overlap and exposed in the phono column alongside text. The source grids additionally carry phones, syll and words tiers.
  • read — Read speech (prompted reading). One phrase per file with normalized, lower-cased transcripts.
  • spon — Spontaneous speech (radio, TV, dictaphone, etc.). One phrase per file with normalized, lower-cased transcripts.

Data Instances

A representative example (the audio.array waveform is shown truncated):

{
  'audio': {
    'path': 'audio/dial/A/F3/A0401-SDF3/A0401-SDF3-0001.flac',
    'array': array([0.00012, -0.00008, ..., 0.00031], dtype=float32),
    'sampling_rate': 44100,
  },
  'text': "nuˈsteps ˈman' baˈtarke",
  'category': 'dial',
  'speaker_id': 'A04', 'gender': 'Female', 'age_group': '18-60',
  'lang_type': 'Spontaneous', 'source': 'Dictaphone',
  'region': 'Aukštaitija', 'county': '',
  'file_path': 'audio/dial/A/F3/A0401-SDF3/A0401-SDF3-0001.flac',
  'file_hash': '', 'segment_id': '', 'start_ms': 0, 'end_ms': 0,
  'duration_ms': 1492,
}

Data Fields

The configs do not all share one schema: within each part a field is populated only where the source encodes it. Field meanings first, then a per-config availability matrix.

Field Type Description
audio Audio Decoded to a waveform array + sampling_rate (44100), backed by mono FLAC bytes.
text string Transcript (normalized; dial = phonetic/dialectal).
phono string Phonetic transcription, SAMPA-style, from the TextGrid phono tier (phon = per phrase).
category string Corpus part: dial / phon / read / spon.
speaker_id string Speaker code, where the path encodes one.
gender string Male / Female.
age_group string 0-12 / 13-17 / 18-60 / 60+.
lang_type string Read / Spontaneous / Mixed.
source string Studio / Dictaphone / Radio / TV / Phone / Audiobook / Unknown.
region string Dialect region: Aukštaitija / Dzūkija / Suvalkija / Žemaitija.
county string County of the speaker.
file_path string Original path of the clip inside the corpus archive.
file_hash string Content-hash id of the source recording.
segment_id string Phrase index within the source recording.
start_ms / end_ms int32 Phrase boundaries within the source recording.
duration_ms int32 Clip duration in milliseconds.

Field availability by config

● populated · ○ present but always empty · – not a column in this config.

Field dial phon read spon
audio ● ● ● ●
text ● ● ● ●
phono – ● – ○
category ● ● ● ●
speaker_id ● ○ ● ○
gender ● ● ○ ●
age_group ● ● ○ ●
lang_type ● ● ○ ●
source ● ● ○ ●
region ● ○ ○ ○
county ○ ○ ● ○
file_path ● ● ● ●
file_hash ○ ● ○ ●
segment_id ○ ● ○ ○
start_ms / end_ms ○ ● ○ ○
duration_ms ● ● ● ●

Data Splits

Each config has a single train split. Exact per-config row/byte counts appear in the viewer's Dataset Structure panel. Full-corpus totals:

Part Duration (h:m:s) Speakers Phrases Words Files Size (FLAC 44.1k)
Dialectal (dial) 100:29:24 117 111,970 916,343 111,970 15 GB
Phonetic (phon) 501:08:59 500+ 1,084,228 4,383,938 145,644 74 GB
Read (read) 5015:37:12 7,125 2,699,385 26,984,811 2,699,385 578 GB
Spontaneous (spon) 4937:25:27 5,000+ 4,527,544 43,135,179 4,527,544 608 GB

Audio Format

FLAC, 44.1 kHz, 16-bit, mono (source quality). Phrase durations (source): dial avg 3.23 s, read avg 6.69 s, spon avg 3.93 s.

Dataset Creation

Curation rationale. Advance Lithuanian speech technology (ASR/TTS) and provide a phonetically representative, openly-licensed resource for a comparatively low-resource language.

Source data. Recordings gathered from many sources/conditions — studio, dictaphone, radio and TV, telephone and audiobooks — to maximize acoustic diversity. Encoding codes in file paths capture language type, source, gender, age group and region/county.

Annotations. Phrase-level transcription covers all 10,000 h. The phonetic (phon) part (500 h) additionally provides word, syllable and phoneme annotations as Praat TextGrid files (phoneme set per Kasparaitis 2005, 92 units). The dial part adds dialectal phonetic transcription.

Personal and sensitive information. Speakers are referenced only by anonymized codes. Spontaneous/broadcast material may mention real people or events; use responsibly.

Considerations for Using the Data

Social impact. Openly-licensed, large-scale Lithuanian speech data — a comparatively low-resource language — lowers the barrier to accessible voice interfaces, transcription and assistive technology, and supports Baltic-language speech research.

Distribution & biases. Aggregate gender balance by part (hours):

Part Total h Male h (%) Female h (%)
dial 100 23 (23%) 77 (77%)
phon 501 291 (58%) 210 (42%)
read 5,015 2,154 (43%) 2,842 (57%)
spon 4,937 2,552 (52%) 2,385 (48%)

Source/condition coverage is uneven (read speech dominates total hours); account for domain and speaker imbalance when training/evaluating.

Known limitations. phon clips are sliced on the TextGrid ortho tier; normalized transcripts drop casing/punctuation (except dial); demographics are only as complete as the original path encoding.

Additional Information

Official Release

The authoritative dataset is distributed via the CLARIN-LT repository: https://clarin-repo.lt/items/0a04648e-ba4e-4e6f-9161-a2d01e8e9fdb/full

Original Documentation

The authoritative corpus documentation is bundled in this repository:

Dataset Curators

Created 2025–2026 by Vytautas Magnus University (VDU), Vilnius University (VU) and the Institute of the Lithuanian Language (LKI).

Licensing Information

Released under Creative Commons Attribution 4.0 International (CC BY 4.0). Share and adapt for any purpose with appropriate credit to the LIEPA-3 authors.

Citation 

@misc{liepa3,
  title        = {Didysis lietuvių kalbos garsynas (LIEPA-3)},
  author       = {Vytautas Magnus University and Vilnius University and
                  Institute of the Lithuanian Language},
  year         = {2026},
  note         = {Large Lithuanian speech corpus, ~10,000 hours},
  howpublished = {CC BY 4.0}
}

Contributions

Packaged for the 🤗 datasets library from the original FLAC corpus. See the bundled original documentation for authoritative details.