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.

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

• Sample scale. 90 clips, 15 speakers, 3.5 hours. Enough for evaluation and for alignment work; not a training corpus.
• Speaker origin is concentrated in this sample. Every contributor here records a Metro Manila or English-speaking origin — natively bilingual Cebuano speakers based outside the Cebuano-speaking regions. That is a real and commercially relevant population, but it is not in-region recording. Contributors based in the Central Visayas and Mindanao are present in Silencio's wider Cebuano inventory and reachable through the collection programme described below; they are simply not in this sample.
• Proficiency is self-declared and not independently assessed.
• Word timings are machine-generated. Forced alignment with wav2vec2_mms, not manually corrected. Token counts reconcile exactly against the human reference on every clip, but individual boundaries have not been human-verified.
• Unbalanced contribution. Clips per speaker ranges from 5 to 7.
• No acoustic annotation. Recording environment, background-noise class and SNR are not annotated. Available for commissioned collection.
• Mixed audio format. Source audio is shipped untouched at its captured sample rate and channel count — see the spec table. Resample and downmix before batching.
• No diarisation. Single speaker per clip. Multi-speaker material is part of the collection programme described below, not this release.
• Pseudonymous speakers. speaker_id values are pseudonyms, coherent within this dataset, deliberately not linkable to speakers in other Silencio releases.
• No baseline. No reference WER is published with this release.

Provenance and consent

Every recording is contributed by an opted-in participant through the Silencio app, 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: info@silencio.network

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 inventory as of August 2026:

Language / variety	Hours	Recordings	Speakers
Tagalog / Filipino	2,135	192,264	5,507
Philippine English	2,705	129,433	2,340
Cebuano	505	31,668	614
Hiligaynon	12	1,600	51
Ilocano	11	1,186	50

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.

Language	Single-speaker	Multi-speaker	Total
Cebuano	1,000 h	1,500 h	2,500 h
Tagalog	1,000 h	1,500 h	2,500 h
Hiligaynon	1,000 h	1,500 h	2,500 h
Total	3,000 h	4,500 h	7,500 h

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

Silencio corpus and collection network

Two distinct figures, because they answer different questions.

Recorded and available off the shelf — audio already collected, with metadata, licensable today:

Hours recorded	127,793
Recordings	9,392,870
Contributors who recorded	222,145
Languages	156
Countries and territories of origin	216

Contributor network available for commissioned collection — registered, consented contributors who can be activated for a specific brief. These are not active contributors to the corpus above; they are the pool it is drawn from and extended through:

Registered contributors	2,000,000+
Countries	180+
Languages reachable	250+

For volume licensing, pre-release access to the Philippines programme, or commissioned collection in a language not listed: info@silencio.network