Dataset Viewer
Auto-converted to Parquet Duplicate
audio
audioduration (s)
764
3.06k
country_from
stringclasses
1 value
country_to
stringclasses
1 value
topic
stringclasses
4 values
languages
listlengths
1
1
duration_seconds
float64
764
3.06k
turns_per_minute
float64
6.1
10.5
turn_taking_gap_ms
int64
378
1.47k
speech_balance_percent
float64
33.5
48.3
overlap_percent
float64
6
15
language
stringclasses
1 value
VN
VN
business_finance
[ "vi" ]
763.632
10.5
378
39.4
15
vi
VN
VN
business_finance
[ "vi" ]
1,705.176
9.4
383
47.2
12.9
vi
VN
VN
games_hobbies
[ "vi" ]
1,329.72
10
973
43.8
9.7
vi
VN
VN
technology_science
[ "vi" ]
2,467.128
9.7
1,248
48.3
7.7
vi
VN
VN
mixed
[ "vi" ]
930.168
6.3
495
33.8
7.5
vi
VN
VN
games_hobbies
[ "vi" ]
1,198.968
7.9
1,465
43.2
7.7
vi
VN
VN
games_hobbies
[ "vi" ]
3,064.152
8
1,173
45.3
6
vi
VN
VN
mixed
[ "vi" ]
968.88
6.1
581
33.5
8.8
vi

DataHive — Vietnamese Conversations

Unscripted conversations in Vietnamese between people who already know each other. Shared to support research on natural conversational voice models.

Why These Conversations

Natural conversation depends on timing: when to respond, brief acknowledgments, pauses, and interruptions. People who know each other share context, leave thoughts unfinished, and switch turns without explicit signals. These recordings capture that.

How We Collect

Participants call people they know through the Hive Calls app (Google Play, App Store). They choose their own topics, with no scripts. Conversations take place in everyday environments and are recorded through LiveKit, with each participant saved separately using Opus compression in an Ogg container. These recordings are converted to stereo MP3 for this sample. Participants are paid for qualifying conversation time.

What’s in This Sample

Detail Value
Language Vietnamese (vi)
Conversations 8
Speakers 8 unique speakers
Total duration 3h 27m 8s
Conversation length 12m 44s–51m 4s
Audio Stereo MP3 · 48 kHz · 128 kbps
Channels Caller left, callee right, on a shared timeline
Metadata JSONL, one record per conversation
License CC BY 4.0

Metadata per conversation:

  • topic
  • language: conversation language code (vi)
  • languages: detected language codes from the original export
  • duration
  • caller and callee country (from phone number)
  • turns per minute
  • median gap between turns
  • speech balance
  • overlap

Transcripts are not included.

Files

README.md
preview/metadata.jsonl
preview/vi_000001.mp3
preview/vi_000002.mp3
...

Install the Hugging Face audio dependencies, then load the dataset from the extracted folder:

python -m pip install "datasets[audio]"
from datasets import load_dataset

ds = load_dataset("audiofolder", data_dir="preview")

Quality and Selection

Every conversation passes QA review and automated checks for:

  • Audio: noise, signal-to-noise ratio, clipping, silence.
  • Dynamics: both speakers participate, turn-taking, overlap, interruptions, gaps.
  • Content: the same language on both tracks, topic, explicit content.

Conversations are at least two minutes long. Repeat appearances by the same speaker are limited. Labels and measurements are automatic.

Consent and Privacy

Participants explicitly consent to recording, sharing with customers, and AI model training. Conversations flagged for personal information are excluded. Metadata contains no names, phone numbers, or account IDs. Audio and transcript redaction is available on request.

Custom Collections

We collect conversations for voice-model labs by language, accent, and requirements. Deliverables can include separate speaker tracks, transcripts, and quality metadata. On request, we can arrange collection of audio captured on-device before lossy compression, delivered as PCM WAV or FLAC. Contact contact@datahive.ai.

License

Released under CC BY 4.0. Free for research and commercial use, including model training, with attribution to DataHive.

Downloads last month
25