SilencioNetwork/cebuano-speech

Cebuano (Bisaya) Spontaneous Speech — Silencio Philippines Pack

Spontaneous long-form Cebuano with human transcription and word-level forced alignment. Fifteen speakers, mean clip length over two minutes, 27,000+ timestamped tokens. Part of the Silencio Philippines Pack.

Hours	3.48
Clips	90
Speakers	15
Countries	2
Speaker origin regions	4
L1 speakers of the recorded language	11 of 15 (65 clips)
Audio	48 kHz stereo WAV
Mean clip length	139.2 s
Transcripts	human_validated: 90
Licence	cc-by-nc-4.0

All 90 clips carry a human transcription.

Recordings are unscripted responses to open prompts, captured on contributors' own devices in their own environments. Mean clip length is 139 seconds — long-form spontaneous speech, not short read utterances.

This is a sample, not the catalogue. It is drawn to show format, audio quality and metadata, and its speaker mix does not represent what Silencio holds. The off-the-shelf catalogue behind it is far more diverse across regions, age groups, accents and recording conditions. Men are 60% of the speakers in this sample. Across the catalogue the gender split is roughly 40% female to 60% male, with men in the majority in most languages. Licensed subsets can be drawn to a specified gender, age or regional balance.

Load it

from datasets import load_dataset

ds = load_dataset("SilencioNetwork/cebuano-speech", split="train")
print(ds[0]["transcript"], ds[0]["dialect"], ds[0]["country"])

# datasets v4 returns a torchcodec AudioDecoder:
s = ds[0]["audio"].get_all_samples()
audio, sr = s.data, s.sample_rate

Requires pip install "datasets>=4.0" and FFmpeg ≥ 4.

Speaker and recording metadata

By country

Country	Speakers	%
Philippines	14	93.3%
Asia/Pacific Region	1	6.7%

Speaker origin / self-reported variety — this is the speaker's own background, not a dialect classification of the recorded language

Speaker origin	Speakers	%
Philippines - Manila (Tagalog)	11	73.3%
Philippines - Visayan English	2	13.3%
Philippines - Filipino English (Manila)	1	6.7%
United States - General American	1	6.7%

Demographics

Gender	Speakers	%
male	9	60.0%
female	6	40.0%

Age band	Speakers	%
25-34	5	33.3%
35-44	4	26.7%
18-24	4	26.7%
45-59	2	13.3%

Recording conditions

Device	Clips	%
Mobile	67	74.4%
Desktop	23	25.6%

Splits

Single split, test, 90 rows. No train/dev/test partition is provided: at this scale a partition would leave each part too small to be meaningful. Speaker identifiers are stable, so a speaker-disjoint split can be constructed at load time.

Fields

Column	Description	Values in this release
audio	Audio payload. Stored at source rate; see the spec table for the exact distribution	48 kHz stereo WAV
speaker_id	Pseudonymous speaker identifier. Coherent within this dataset; deliberately not linkable to other Silencio releases	15 distinct
language	Language of the recording	constant: Cebuano
transcript	Human transcription of the recording	90 distinct
transcript_type	Provenance of the transcript	constant: human_validated
gender	Self-reported	female, male
country	Speaker's country	Asia/Pacific Region, Philippines
mother_tongue	Speaker's self-reported first language	English, Tagalog / Filipino
dialect	Self-reported speaker origin / regional variety. This is the speaker's own background, NOT a dialect classification of the recorded language	Philippines - Filipino English (Manila), Philippines - Manila (Tagalog), Philippines - Visayan English, United States - General American
os	Operating system of the recording device	Linux, Windows
device	Recording device class	Desktop, Mobile
duration	Seconds	89 distinct
script_type	Elicitation style	constant: free_speech
words	Word-level forced alignment: text, normalised text, start and end in seconds	26,618 entries across 90 clips
n_words	Number of aligned tokens in this clip	82 distinct
transcript_model	How the transcript text was produced	constant: human
aligner	Model used to produce the word timings	constant: wav2vec2_mms
age_band	Self-reported age, banded	18-24, 25-34, 35-44, 45-59
native_speaker	True where mother_tongue matches the recorded language	2 distinct
proficiency	Speaker's self-declared proficiency in the recorded language	conversational, fluent, native

Related Cebuano and Philippine speech resources

Cebuano (Bisaya, Binisaya) has roughly 20 million speakers across the Central Visayas, Negros Oriental and much of Mindanao — the second most widely spoken language in the Philippines. Existing Hub coverage:

Resource	Scale	Type	Licence
google/fleurs (ceb_ph)	4,027 utterances	Read Wikipedia sentences, short utterances	CC BY 4.0
sil-ai/bloom-speech	Multilingual	Children's book narration	Varies
espnet/mms_ulab_v2	Multilingual	Unlabelled audio	—
This dataset	90 clips, 3.5 h, 139 s mean	Spontaneous long-form, word-level alignment, speaker metadata	CC BY-NC 4.0

There is no single-language Cebuano audio dataset on the Hub. FLEURS is the closest usable resource and is read speech in short utterances; this release is unscripted long-form speech with per-word timings. The two are complementary rather than competing — FLEURS for read-speech benchmarking, this for spontaneous-speech behaviour.

Also from Silencio. Tagalog / Filipino is published under this same protocol — spontaneous speech, human transcription, word-level alignment. Hiligaynon and expanded Cebuano follow; see SilencioNetwork.

Transcription and alignment

Two distinct provenances, kept separate because they carry different confidence.

Text — human. Every transcript was produced by a human annotator listening to the recording. The transcript_model column records this per clip.

Timings — machine. Word-level start and end times come from forced alignment with wav2vec2_mms, recorded per clip in the aligner column. On every clip in this release the aligner's token count matches the human reference token count exactly, and no word timing runs past the end of its audio file.

The words column holds one entry per token with text, normalized_text, start and end in seconds. Expand it for segment-level work:

ds = load_dataset("SilencioNetwork/cebuano-speech", split="test")
row = ds[0]
for w in row["words"][:5]:
    print(f"{w['start']:6.2f}-{w['end']:6.2f}  {w['text']}")

Speaker proficiency

Cebuano proficiency is taken from each contributor's own declared language profile, not inferred from a single primary-language field. Most contributors here are natively bilingual: their primary declared language is Tagalog, and they also declare Cebuano at native level.

Declared Cebuano level	Speakers	Clips	Hours
native	11	65	2.16
fluent	3	19	0.82
conversational	1	6	0.50

Filter on native_speaker, or on proficiency for finer control.

What this is useful for

• Spontaneous-speech ASR evaluation. Long-form unscripted Cebuano with human reference text. Models tuned on read speech typically degrade sharply here; that gap is the point.
• Forced-alignment and VAD work. 27,000+ word-level timings over 3.5 hours.
• Long-form segmentation. Mean clip length 139 s, with several clips over four minutes. Most Philippine-language audio on the Hub is short read utterances.
• Code-switching and borrowing. Spontaneous Cebuano from bilingual speakers contains substantial Tagalog, Spanish and English material. Not annotated as such in this release.

Limitations

• See the demographic tables above for balance across gender, age and region.

Provenance and consent

Every recording is contributed by an opted-in participant through the Silencio platform, under a consent record covering AI/ML training use. Contributors can request deletion, and deletion propagates to downstream releases. Full provenance documentation is available to licensees.

License

cc-by-nc-4.0 — free for research and non-commercial use with attribution.

Attribution string: Silencio Network, Cebuano (Bisaya) Spontaneous Speech, 2026. CC BY-NC 4.0.

Non-commercial covers research, evaluation and publication. Benchmarking a commercial product model against this data is a commercial use and needs a licence — ask, it is usually granted for evaluation. Model weights trained on this sample inherit the non-commercial restriction. Contributors may withdraw consent; withdrawal propagates to subsequent releases but places no retroactive obligation on an existing licensee.

Commercial licensing, including terms for models trained on this data: silencio.network/contact

Citation

@misc{silencio_cebuano_2026,
  title  = {Cebuano (Bisaya) Spontaneous Speech — Silencio Philippines Pack},
  author = {Silencio Network},
  year   = {2026},
  url    = {https://huggingface.co/datasets/SilencioNetwork/cebuano-speech}
}

The Silencio Philippines Pack

Philippine catalogue depth, September 2026, shown as bands:

Language / variety	Catalogue band
Tagalog / Filipino	Tier 3, 1,500 to 5,000 h
Philippine English	Part of English multi-country, Tier 1
Cebuano	Tier 3, 1,500 to 5,000 h
Hiligaynon, Ilocano	Less than 500 h

In active collection: 7,500 hours. A collection and human-transcription programme covering 2,500 hours each of Cebuano, Tagalog and Hiligaynon, split per language into 1,000 hours single-speaker and 1,500 hours multi-speaker.

Human-validated transcription is available for every language, scoped to the client's needs, and every clip in delivery is validated by a native-speaker human reviewer.

Ilocano, Waray, Bikol, Kapampangan and Pangasinan are available through commissioned collection.

Silencio: the catalogue behind this sample

This listing is a small fraction of what Silencio provides. Silencio specialises in underrepresented languages, accents and niche domains, delivered at scale. It draws on the largest global community of speech contributors and holds the largest off-the-shelf catalogue of niche-language speech available.

Recorded and available off the shelf. Audio already collected, with metadata, licensable today. Catalogue position as of September 2026:

Hours, off the shelf	around 500,000
Countries of contributor origin	around 180
Catalogue refresh	Weekly at record level, quarterly at catalogue level

Contributor community available on demand. Registered, consented contributors who can be activated for a specific brief:

Contributors available on demand	around 2,500,000
Countries	180+
Languages that can be collected	around 350

Anything not off the shelf can be sourced through the community. A language, an accent or dialect region, a demographic, a recording condition, a speech style or a specialist domain can be collected to a client's brief. Deep coverage across Africa, South-East Asia, South Asia and the Middle East.

Human-validated transcription is available for every language, scoped to each client's needs: script and orthography conventions, normalisation rules, word- or segment-level alignment, speaker labelling and turnaround. Every delivered clip is checked by a native-speaker reviewer. Published samples with human-validated transcripts: Kenyan Swahili, Cebuano, Tagalog / Filipino, Yoruba, Hausa and Amharic.

Proprietary and first-party. Every recording is collected directly by Silencio from consenting contributors. Nothing is scraped, and these recordings are not available in any other dataset on the internet.

Ethical sourcing, with provenance records. Every recording carries a consent record covering AI/ML training use, and contributor-level provenance documentation is available to licensees, including for EU AI Act training-data summaries. Contributors can withdraw consent, and withdrawal propagates to subsequent releases.

More at silencio.network.

For volume licensing, bespoke transcription or commissioned collection: silencio.network/contact