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mp3 audio | json dict | ref.mp3 audio | ref.json dict | __key__ string | __url__ string |
|---|---|---|---|---|---|
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"text": " Das Drakonita-Bademekum soll demnächst als PDF bei den Bäckern eintreffen. Und Hauptbucheskammer und Helden-Brivier sind ebenfalls schon sehr weit und durchs Lektorat, während das Regional-Abenteuer und Pubertschan und Helden-Sagen, also das Meister-Set, ebenfalls auch schon den Regeltest bestanden haben. Und auch die Netanernachrichten sind schon sehr weit.",
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} | DE_B00000_S00000_W000023 | hf://datasets/laion/emolia-hq@c23c1098110c8b9f94789054009dcf7358da8090/DE/DE-B000000_standard_hq.tar | ||
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"text": " Dann haben wir das Gebiet an die Tiefe, das kommende Heldenwerk, das wurde ja hier schon gespoilert im F-Shop. Jetzt haben wir hier auch das Cover, das Korrekte und ein paar Insights, ein paar Bilder daraus, beziehungsweise das Bild soll wohl gar nicht aus dem Abenteuer sein, aber man kann so ein bisschen sich denken, worum es vielleicht gehen könnte.",
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},
"emotion_caption": "A medium-quality recording of a single speaker, a male, speaking in a somewhat monotone voice. The audio quality is decent, and there is no background noise.",
"id": "DE_B00000_S00000_W000030",
"language": "de",
"language_id": "DE",
"speaker": "DE_B00000_S00000",
"speaker_id": "DE_B00000_S00000",
"text": " Ein Seemafora vorher noch, genau, dann ein Stadtplan von Tegun. Und auch das Oktagon der Drakonita ist dort im Video gezeigt worden. Wie gesagt, wer Näheres dazu wissen will, schaut auf YouTube oder Twitch rein.",
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},
"emotion_caption": "A low-quality recording of a single, sustained, and somewhat distorted musical note. It sounds like a synthesized tone or a very low-frequency hum.",
"id": "DE_B00000_S00000_W000023",
"language": "de",
"language_id": "DE",
"speaker": "DE_B00000_S00000",
"speaker_id": "DE_B00000_S00000",
"text": " Das Drakonita-Bademekum soll demnächst als PDF bei den Bäckern eintreffen. Und Hauptbucheskammer und Helden-Brivier sind ebenfalls schon sehr weit und durchs Lektorat, während das Regional-Abenteuer und Pubertschan und Helden-Sagen, also das Meister-Set, ebenfalls auch schon den Regeltest bestanden haben. Und auch die Netanernachrichten sind schon sehr weit.",
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} | DE_B00000_S00000_W000030 | hf://datasets/laion/emolia-hq@c23c1098110c8b9f94789054009dcf7358da8090/DE/DE-B000000_standard_hq.tar |
End of preview.
Emolia-HQ
Emolia-HQ is a high-quality, speaker-paired subset of the LAION Emolia dataset. Each sample includes a target utterance and a reference utterance from the same speaker, enabling speaker-conditioned tasks such as voice conversion, expressive TTS, and speaker-aware emotion recognition.
Source
Derived from laion/Emolia by:
- Quality filtering: Only samples with
dnsmos >= 3.0are retained. - Speaker pairing: Each target sample is matched with a reference audio from the same speaker (different utterance), forming a "quadruplet". Samples where no same-speaker reference exists are included as pairs (target only).
- Metadata enrichment:
speaker_idandlanguage_idfields are extracted from the key and injected into each sample's JSON metadata.
Data Format
The dataset is stored as WebDataset .tar files, organized by language:
emolia_hq/
DE/ # German (243 tars, ~130 GB)
EN/ # English (2,380 tars, ~2,476 GB)
FR/ # French (298 tars, ~187 GB)
JA/ # Japanese (96 tars, ~163 GB)
KO/ # Korean (246 tars, ~79 GB)
ZH/ # Chinese (929 tars, ~1,681 GB)
Each sample within a tar file is grouped by a shared base key:
Quadruplet (target + same-speaker reference)
| File | Description |
|---|---|
<key>.mp3 |
Target audio |
<key>.json |
Target metadata |
<key>.ref.mp3 |
Reference audio (same speaker, different utterance) |
<key>.ref.json |
Reference metadata |
Pair (no reference found)
| File | Description |
|---|---|
<key>.mp3 |
Target audio |
<key>.json |
Target metadata |
JSON Metadata Fields
| Field | Description |
|---|---|
id |
Unique utterance ID |
text |
Transcription |
duration |
Audio duration in seconds |
dnsmos |
DNS-MOS quality score (all >= 3.0) |
speaker |
Original speaker ID |
speaker_id |
Extracted speaker ID (e.g., DE_B00000_S00010) |
language_id |
Extracted language code (e.g., DE) |
language |
Language code lowercase |
emotion_caption |
Natural language description of the emotional content |
emotion_annotation |
Dictionary of 50+ emotion/prosody scores |
characters_per_second |
Speaking rate |
wavelm_timbre_embedding |
128-dim speaker timbre embedding |
Statistics
| Language | Tars | Size |
|---|---|---|
| DE (German) | 243 | ~130 GB |
| EN (English) | 2,380 | ~2,476 GB |
| FR (French) | 298 | ~187 GB |
| JA (Japanese) | 96 | ~163 GB |
| KO (Korean) | 246 | ~79 GB |
| ZH (Chinese) | 929 | ~1,681 GB |
| Total | 4,192 | ~4,716 GB |
~97% of samples include a same-speaker reference audio (quadruplets). The remaining ~3% are pairs where the speaker only appeared once across the entire dataset.
Usage
import webdataset as wds
dataset = wds.WebDataset("emolia_hq/EN/EN-B000000_standard_hq.tar")
for sample in dataset:
key = sample["__key__"]
target_audio = sample["mp3"] # bytes
target_meta = sample["json"] # bytes -> json.loads()
ref_audio = sample.get("ref.mp3") # bytes or None
ref_meta = sample.get("ref.json") # bytes or None
License
Same as the source Emolia dataset. See laion/Emolia for details.
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