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12.5
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6.16
12.5
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vp_train_168289
All of this is positive, yet there are very significant challenges that persist.
20190313-0900-PLENARY-en_20190313-15:59:22_13
6.16
en
female
None
true
All of this is positive, yet there are very significant challenges that persist.
all of this is positive yet there are very significant challenges that persist.
[ { "word": "All", "start": 0.32, "end": 0.48, "score": 0.9539016783237457 }, { "word": "of", "start": 0.48, "end": 0.56, "score": 0.8613452315330505 }, { "word": "this", "start": 0.64, "end": 0.96, "score": 0.8129779100418091 }, { "word": "is", "sta...
28116
voxpopuli
vp_train_168290
At the same time, I want to reassure you that the EU listing has no punitive intention.
20180205-0900-PLENARY-20-en_20180205-23:15:35_13
7.12
en
female
None
true
At the same time, I want to reassure you that the EU listing has no punitive intention.
at the same time i want to reassure you that the eu listing has no punitive intention.
[ { "word": "At", "start": 0.32, "end": 0.48, "score": 0.9807382822036743 }, { "word": "the", "start": 0.48, "end": 0.56, "score": 0.9798922836780548 }, { "word": "same", "start": 0.56, "end": 0.88, "score": 0.9870938062667847 }, { "word": "time", "s...
inferred_00006
inferred_cluster
vp_train_168291
The Presidency expressed this sentiment through a statement which was issued shortly after President Obama signed the Executive Orders.
20090203-0900-PLENARY-9-en_20090203-15:03:26_4
12.4795
en
male
None
true
The Presidency expressed this sentiment through a statement which was issued shortly after President Obama signed the Executive Orders.
the presidency expressed this sentiment through a statement which was issued shortly after president obama signed the executive orders.
[ { "word": "The", "start": 0.08, "end": 0.32, "score": 0.4828017055988312 }, { "word": "Presidency", "start": 0.48, "end": 1.2, "score": 0.5694943368434906 }, { "word": "expressed", "start": 1.2, "end": 1.84, "score": 0.6227274239063263 }, { "word": "th...
95116
voxpopuli
vp_train_168294
And then state-linked media labelled these women as traitors, and they have since been charged with serious crimes.
20180531-0900-PLENARY-4-en_20180531-10:51:33_1
6.3
en
male
None
true
Then, state linked media labelled these women as traitors, and they have since been charged with serious crimes.
then state linked media labelled these women as traitors and they have since been charged with serious crimes.
[ { "word": "And", "start": 0.24, "end": 0.4, "score": 0.9512798190116882 }, { "word": "then", "start": 0.4, "end": 0.64, "score": 0.8760237395763397 }, { "word": "statelinked", "start": 0.8, "end": 1.44, "score": 0.9347124099731445 }, { "word": "media",...
96945
voxpopuli
vp_train_168295
Consequently, I am concerned that extending the EPO to cover civil matters would lead to confusion.
20130522-0900-PLENARY-3-en_20130522-08:51:45_8
7.860063
en
female
None
true
Consequently, I am concerned that extending the EPO to cover civil matters would lead to confusion.
consequently i am concerned that extending the epo to cover civil matters would lead to confusion.
[ { "word": "Consequently", "start": 0.16, "end": 1.12, "score": 0.9238126277923584 }, { "word": "I", "start": 1.36, "end": 1.52, "score": 0.6312651336193085 }, { "word": "am", "start": 1.52, "end": 1.6, "score": 0.8602012693881989 }, { "word": "concerne...
96944
voxpopuli

VoxPopuli-Platinum-en

Showcase page and playable sample rows for the full 142,066-row / ~404-hour English VoxPopuli Platinum dataset.

Reach out to data@trelis.com to purchase access or discuss a larger custom-curation engagement.

Training Results

These results show why the Platinum labels matter. We compare the base model, fine-tuning on raw VoxPopuli transcripts, and fine-tuning on this internally filtered Platinum dataset. Evaluation uses the same english-spoken corpus WER setup across four held-out ASR test sets.

WER comparison across raw and Platinum fine-tuning

Qwen3-ASR-0.6B WER

Training data VP-test FLEURS CV-scripted CV-spontaneous
Base model, no fine-tune 2.39% 4.40% 7.31% 9.16%
Raw VoxPopuli transcripts 4.49% 4.70% 19.45% 16.77%
VoxPopuli Platinum 2.17% 4.02% 7.73% 9.90%

Whisper Large v3 Turbo WER

Training data VP-test FLEURS CV-scripted CV-spontaneous
Base model, no fine-tune 8.26% 4.41% 8.38% 10.93%
Raw VoxPopuli transcripts 3.77% 7.08% 15.75% 24.27%
VoxPopuli Platinum 3.12% 5.90% 11.41% 11.36%

Raw VoxPopuli labels are useful in-domain but can damage out-of-domain behavior. The Platinum set is filtered with Trelis internal heuristics to keep the useful VoxPopuli signal while rejecting or repairing label/audio mismatches. The training results above are the evidence for that quality filter; the filtering recipe itself is proprietary.

Contents

  • 10 parquet shards: data/train-00000.parquet through data/train-00009.parquet
  • 142,066 rows / about 404 hours
  • 16 kHz English speech from VoxPopuli
  • Cleaned training text
  • Word-level timestamps
  • Speaker IDs for every row
  • Original VoxPopuli raw_text and normalized_text for auditability

Recommended Use

This dataset is suitable for ASR fine-tuning, timestamp-aware ASR experiments, captioning/alignment workflows, speaker-aware filtering, and TTS experiments. For TTS, treat it as parliamentary speech with cleaned text and speaker IDs, not as studio-recorded voice-cloning data.

Speaker IDs

source rows meaning
voxpopuli 91,482 Original VoxPopuli speaker ID was present and preserved
inferred_matched 16,104 Missing-source row was matched to an existing speaker identity
inferred_cluster 34,480 Missing-source row was assigned to an inferred speaker cluster

The speaker_id_source column tells you whether the speaker ID came directly from VoxPopuli or was inferred by Trelis.

Schema

field description
id Trelis row ID
audio 16 kHz audio
text cleaned ASR/TTS training text
voxpopuli_id original VoxPopuli audio_id
duration_s clip duration
language en
gender, accent, is_gold_transcript source VoxPopuli metadata
voxpopuli_raw_text original VoxPopuli raw transcript text
voxpopuli_normalized_text original VoxPopuli normalized transcript text
word_timestamps list of {word, start, end, score}
speaker_id preserved or inferred speaker ID
speaker_id_source voxpopuli, inferred_matched, or inferred_cluster

License

Commercial Trelis license required. Redistribution is not permitted.

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